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Journal articles on the topic 'Signal processing Mathematical models'
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1
Rogozinsky, G., M. Chesnokov, and A. Kutlyiarova. "Some New Mathematical Models of Synthesized Sound Signals." Proceedings of Telecommunication Universities 8, no. 2 (June 30, 2022): 76–81. http://dx.doi.org/10.31854/1813-324x-2022-8-2-76-81.
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Modern sound synthesis systems make it possible to implement various signal generation algorithms of higher complexity. The theory of sound synthesis actively uses the mathematical apparatus of analog and digital radio engineering and signal processing, however, it should be noted that the classical signal models used in acoustics are not adequate to real-world synthesized signals, mainly due to the significant complexity of the latter. This article presents some models of synthesized signals typical for practical use.
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Monakov, A. A., and A. A. Tarasenkov. "Comparative Analysis of Mathematical Models of Tracking Radio Altimeters." Journal of the Russian Universities. Radioelectronics 25, no. 4 (September 29, 2022): 72–80. http://dx.doi.org/10.32603/1993-8985-2022-25-4-72-80.
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Introduction. Tracking radio altimeters of low altitudes are widely used in civil aviation. These devises use periodic frequency modulated continuous wave (FMCW) signals, while altitude measurements are based on processing the beat signal processing. For this purpose, a closed automatic control loop is arranged to maintain the frequency of the beat signal at a fixed level by changing parameters of the transmitted signal (the frequency deviation or the modulation period). An alternative approach to arranging the tracking loop for altitude variations is based on the use of a phase locked loop (PLL), which adjusts the reference signal – a copy of the emitted signal – to obtain the maximum cross-correlation of the beat and reference signals. А comparative analysis of short-range radio altimeters with other currently known tracking radio altimeters for various types of frequency modulation of the transmitted signal seems to be a relevant research task.Aim. An analysis of the influence of the type of frequency modulation on the accuracy of altitude estimation in a PLL-based radar altimeter, as well as a comparative analysis of this altimeter with other known tracking altimeters.Materials and methods. Mathematical models of tracking radio altimeters are proposed, and a computer simulation of their performance is carried out for the case of altitude estimation over a smooth flat surface.Results. The conducted comparative analysis of tracking radio altimeters confirmed the effectiveness of the PLL when processing signals of different frequency modulation type (sawtooth, triangular, and harmonic FM). Altitude estimates produced by PLL-based radar altimeters are unbiased, with their standard deviation not exceeding 3 cm for the signalto-noise ratio of greater than 10 dB and under the scenario parameters adopted in the work. The conducted comparison with other tracking altimeters showed that estimation errors of this radar altimeter are an order of magnitude smaller.Conclusion. A PLL-based tracking radar altimeter can be used to estimate the height of the aircraft flight. The quality of altitude estimates produced by this device is higher than those produced by other known tracking radio altimeters. Further research and field tests will investigate the accuracy of altitude estimation when working over a rough surface.
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Qu, Qiuhui. "Application of MATLAB in signal and system." SHS Web of Conferences 145 (2022): 01029. http://dx.doi.org/10.1051/shsconf/202214501029.
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Signal and system course is an important professional basic course for electronic information and communication majors. Signal and system are abstract concepts, which are described by mathematical models. In daily life, simple signals can be calculated or drawn manually, but complex signals are difficult to be accurately processed. Matlab contains graphics processing and symbol operation functions, which provides us with powerful tools to solve the above problems. This paper will introduce how to use Matlab to express, calculate and process signals, and realize the systematic analysis of signals.
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Tague, John A., and Kerry D. Schutz. "Seismic transient deconvolution with model‐based signal processing." GEOPHYSICS 62, no. 4 (July 1997): 1321–30. http://dx.doi.org/10.1190/1.1444234.
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Short duration seismic disturbances, obscured by earth noise and distorted by the seismometers used to measure them, can be reconstructed using model‐based signal processing. “Model based” means that mathematical models of the seismic transient, earth noise, and seismometer dynamics are infused into the signal processor that estimates the disturbance. The processor imposes no predetermined structure on the transient and the earth noise need not be white. Model‐based processors produce good quality estimates for a broad class of transient waveforms.
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Sharko, Artem. "MODELS AND METHODS OF PROCESSING OF INFORMATION ON LOADS OF ACOUSTIC SIGNALS IN TECHNICAL DIAGNOSTIC SYSTEMS." Informatyka Automatyka Pomiary w Gospodarce i Ochronie Środowiska 8, no. 3 (September 25, 2018): 15–18. http://dx.doi.org/10.5604/01.3001.0012.5276.
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The paper presents one-dimensional discrete-continuous model of power spectrum estimation of the acoustic emission signal, that allows filtering the oscillating components of the acoustic emission signals. The mathematical formalism describing the environment was discussed, initiating the signals of acoustic emission. The problem of spectral analysis and synthesis of acoustic emission signals was solved with the help of Fourier transform. The dependence of acoustic vibrations spectra on the size of the medium parameters and microstructure has been discussed, as well.
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Lavanya, S., S. Prabakaran, and N. Ashok Kumar. "A Deep Learning Technique for Detecting High Impedance Faults in Medium Voltage Distribution Networks." Engineering, Technology & Applied Science Research 12, no. 6 (December 1, 2022): 9477–82. http://dx.doi.org/10.48084/etasr.5288.
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Utility companies always struggle with the High Impedance Fault (HIF) in the electrical distribution systems. In this article, the current signal is seen in situations involving 10,400 different samples, with and without HIF, like linear, non-linear load, and capacitance switching. A better method that processes signals very fast and with low sample rates, requiring less memory and computational labor, is demonstrated by Mathematical Morphology (MM). For HIF identification, Deep Convolution Neural Networks (DCNNs) are being developed. This paper presents a novel method for signal processing with low sample rates, high signal processing speed, and low computational and memory requirements. The suggested six-layer DCNN is compared with other models, such as the four-layer and eight-layer DCNN models and the results are discussed.
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Beardah, C. C., and R. M. Thomas. "Two mathematical models of unconfined detonation and their numerical solution." Circuits, Systems, and Signal Processing 13, no. 2-3 (June 1994): 155–65. http://dx.doi.org/10.1007/bf01188103.
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Lomakin, A., D. Pantenkov, and V. Sokolov. "Mathematical Models of Satellite Communication Systems with Unmanned Aerial Vehicles and Counter-Means of Radio Control. Part 2." Proceedings of Telecommunication Universities 5, no. 4 (2019): 37–48. http://dx.doi.org/10.31854/1813-324x-2019-5-4-37-48.
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The article is devoted to the issues of stealth satellite radio channels with unmanned aerial vehicles (UAV) and it is consists of two parts. In the first part of this article the following questions are considered: the general statement of a system development problem of satellite model communication providing its stealth functioning by means of radio monitoring is carried out; the mathimatical apparatus for the assessing the effectiveness of ensuring spatial selectivity in the organization of satellite communication lines at hidden objects of their functioning is presented; the functioning model of the satellite communication system wich use the signal processing methods to ensure the secrecy of its functioning by means of radio monitoring is developed; in the conclusion, proposals and recommendations are formulated to ensure the secrecy of the satellite radio channel with unmanned aerial vehicles. Since the eventual opponent a priori lacks complete reliable information about the radio monitoring signal, the second part of the article considers the methods of quasi-optimal signal processing based on auto-and intercorrelation processing, which allows to obtain a significant energy gain and detect a useful signal even at a very low level of its power at the input. The use of autocorrelation signal processing devices significantly improves the efficiency of radio monitoring (RM), which is especially important in the case of negative ratios of useful signal power and noise at the input of autocorrelation signal processing devices. The main results of the second part of the article include: a mathematical functioning model of the opponent's RM means in the conditions of taking measures to ensure the information transfer secrecy, the parameters calculations results of the satellite system provided that it is hidden from the RM means.
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Al-Suod, Mahmoud, Abdullah Eial Awwad, Alaa Al-Quteimat, and Oleksandr Ushkarenko. "Method for describing signal conversion processes in analog electronic systems." Bulletin of Electrical Engineering and Informatics 11, no. 1 (February 1, 2022): 82–92. http://dx.doi.org/10.11591/eei.v11i1.3545.
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One of the main tasks of information technology is to improve existing and develop new methods for formal recording of various dynamic logical operations of analog and digital signal conversion in electronic control systems, acquisition, and processing of information. The stage of formal recording of any signal transformation process must be presented in the form of analytic symbols, the sequence of which must form a fully functional mathematical model. The improved method of the signals conversion processes description based on a representation of the mathematical models of the electronic circuits’ components in the grapho-analytical form with the increased information content allows integrating the developed models of electronic circuit elements with object-oriented programming language in the form of functional structures. It opens the way to perform parametric analysis of circuits and other tasks, related to the modeling of electronic systems.
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Marano, Stefano, and Marco Marano. "Frontiers in hemodialysis: Solutions and implications of mathematical models for bicarbonate restoring." Biomedical Signal Processing and Control 52 (July 2019): 321–29. http://dx.doi.org/10.1016/j.bspc.2019.02.029.
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Niang, Oumar, Abdoulaye Thioune, Éric Deléchelle, Mary Teuw Niane, and Jacques Lemoine. "About a Partial Differential Equation-Based Interpolator for Signal Envelope Computing: Existence Results and Applications." ISRN Signal Processing 2013 (March 7, 2013): 1–18. http://dx.doi.org/10.1155/2013/605035.
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This paper models and solves the mathematical problem of interpolating characteristic points of signals by a partial differential Equation-(PDE-) based approach. The existence and uniqueness results are established in an appropriate space whose regularity is similar to cubic spline one. We show how this space is suitable for the empirical mode decomposition (EMD) sifting process. Numerical schemes and computing applications are also presented for signal envelopes calculation. The test results show the usefulness of the new PDE interpolator in some pathological cases like input class functions that are not so regular as in the cubic splines case. Some image filtering tests strengthen the demonstration of PDE interpolator performance.
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Konopel'kin, M. Yu, S. V. Petrov, and D. A. Smirnyagina. "Implementation of stochastic signal processing algorithms in radar CAD." Russian Technological Journal 10, no. 5 (October 21, 2022): 49–59. http://dx.doi.org/10.32362/2500-316x-2022-10-5-49-59.
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Objectives. In 2020, development work on the creation of a Russian computer-assisted design system for radars (radar CAD) was completed. Radar CAD provides extensive opportunities for creating simulation models for developing the hardware-software complex of radar algorithms, which take into account the specific conditions of aerospace environment observation. The purpose of the present work is to review and demonstrate the capabilities of radar CAD in terms of implementing and testing algorithms for processing stochastic signals.Methods. The work is based on the mathematical apparatus of linear algebra. Analysis of algorithms characteristics was carried out using the simulation method.Results. A simulation model of a sector surveillance radar with a digital antenna array was created in the radar CAD visual functional editor. The passive channel included the following algorithms: algorithm for detecting stochastic signals; algorithm for estimating the number of stochastic signals; direction finding algorithm for stochastic signal sources; adaptive spatial filtering algorithm. In the process of simulation, the algorithms for detecting and estimating the number of stochastic signals produced a correct detection sign and an estimate of the number of signals. The direction-finding algorithm estimated the angular position of the sources with an accuracy of fractions of degrees. The adaptive spatial filtering algorithm suppressed interfering signals to a level below the antenna's intrinsic noise power.Conclusions. The processing of various types of signals can be simulated in detail on the basis of the Russian radar CAD system for the development of functional radar models. According to the results of the simulation, coordinates of observing objects were obtained and an assessment of the effectiveness of the algorithms was given. The obtained results are fully consistent with the theoretical prediction. The capabilities of radar CAD systems demonstrated in this work can be used by specialists in the field of radar and signal processing.
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Quiroz-Juárez, Mario Alan, Juan Alberto Rosales-Juárez, Omar Jiménez-Ramírez, Rubén Vázquez-Medina, and José Luis Aragón. "ECG Patient Simulator Based on Mathematical Models." Sensors 22, no. 15 (July 30, 2022): 5714. http://dx.doi.org/10.3390/s22155714.
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In this work, we propose a versatile, low-cost, and tunable electronic device to generate realistic electrocardiogram (ECG) waveforms, capable of simulating ECG of patients within a wide range of possibilities. A visual analysis of the clinical ECG register provides the cardiologist with vital physiological information to determine the patient’s heart condition. Because of its clinical significance, there is a strong interest in algorithms and medical ECG measuring devices that acquire, preserve, and process ECG recordings with high fidelity. Bearing this in mind, the proposed electronic device is based on four different mathematical models describing macroscopic heartbeat dynamics with ordinary differential equations. Firstly, we produce full 12-lead ECG profiles by implementing a model comprising a network of heterogeneous oscillators. Then, we implement a discretized reaction–diffusion model in our electronic device to reproduce ECG waveforms from various rhythm disorders. Finally, in order to show the versatility and capabilities of our system, we include two additional models, a ring of three coupled oscillators and a model based on a quasiperiodic motion, which can reproduce a wide range of pathological conditions. With this, the proposed device can reproduce around thirty-two cardiac rhythms with the possibility of exploring different parameter values to simulate new arrhythmias with the same hardware. Our system, which is a hybrid analog–digital circuit, generates realistic ECG signals through digital-to-analog converters whose amplitudes and waveforms are controlled through an interactive and friendly graphic interface. Our ECG patient simulator arises as a promising platform for assessing the performance of electrocardiograph equipment and ECG signal processing software in clinical trials. Additionally the produced 12-lead profiles can be tested in patient monitoring systems.
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Gasanov, A. R., R. A. Gasanov, R. A. Ahmadov, and M. V. Sadikhov. "Mathematical Models of the Acousto-Optic Delay Line Characteristics and Their Adequacy Assessment." Proceedings of Universities. Electronics 26, no. 5 (2021): 410–25. http://dx.doi.org/10.24151/1561-5405-2021-26-5-410-425.
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In radioengineering systems, various methods and technical means are used for signal processing, the selection criteria of which are optimized for the best result of assigned task solution. The study of an analog signal shift on the time axis is one of the widely used radio engineering problems. In this work, the functional capabilities of an acousto-optic delay line (AODL) in the context of processing analog signals in the time domain are listed. The urgency of creating mathematical models of the AODL main characteristics and their study was substantiated. The AODL circuit and its operation principle were discussed, and an expression for the current at its output was obtained. Based on the structural and electrical parameters of the AODL, mathemati-cal models of its transient, impulse and amplitude-frequency characteristics have been con-structed. It was shown that the diameter of the light beam interacting with the elastic wave has the greatest effect on the characteristics of a particular AODL sample. A numerical analysis of the above characteristics was carried out. The results of the numerical analysis were tested expe-rimentally on the AODL model. To avoid accidental coincidences, numerical analysis and expe-rimental approbation were carried out for two values of the laser beam diameter. The adequacy of the transient, impulse and amplitude-frequency characteristics was assessed by the results ob-tained in statics and dynamics. It was shown that the transient, impulse or amplitude-frequency response can be used to determine the AODL frequency and time parameters. Static and dynamic comparison of the results of numerical analysis and experimental studies have shown their unambiguous adequacy.
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Bondar, O. G., E. O. Brezhneva, O. G. Dobroserdov, K. G. Andreev, and N. V. Polyakov. "Synthesis and Parameterization of Gas Sensor Models." Proceedings of the Southwest State University 25, no. 1 (May 30, 2021): 138–61. http://dx.doi.org/10.21869/2223-1560-2021-25-1-138-161.
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Purpose of research: search and analysis of existing models of gas-sensitive sensors. Development of mathematical models of gas-sensitive sensors of various types (semiconductor, thermocatalytic, optical, electrochemical) for their subsequent use in the training of artificial neural networks (INS). Investigation of main physicochemical patterns underlying the principles of sensor operation, consideration of the influence of environmental factors and cross-sensitivity on the sensor output signal. Comparison of simulation results with actual characteristics produced by the sensor industry. The concept of creating mathematical models is described. Their parameterization, research and assessment of adequacy are carried out.Methods. Numerical methods, computer modeling methods, electrical circuit theory, the theory of chemosorption and heterogeneous catalysis, the Freundlich and Langmuir equations, the Buger-Lambert-Behr law, the foundations of electrochemistry were used in creating mathematical models. Standard deviation (MSE) and relative error were calculated to assess the adequacy of the models.Results. The concept of creating mathematical models of sensors based on physicochemical patterns is described. This concept allows the process of data generation for training artificial neural networks used in multi-component gas analyzers for the purpose of joint information processing to be automated. Models of semiconductor, thermocatalytic, optical and electrochemical sensors were obtained and upgraded, considering the influence of additional factors on the sensor signal. Parameterization and assessment of adequacy and extrapolation properties of models by graphical dependencies presented in technical documentation of sensors were carried out. Errors (relative and RMS) of discrepancy of real data and results of simulation of gas-sensitive sensors by basic parameters are determined. The standard error of reproduction of the main characteristics of the sensors did not exceed 0.5%.Conclusion. Multivariable mathematical models of gas-sensitive sensors are synthesized, considering the influence of main gas and external factors (pressure, temperature, humidity, cross-sensitivity) on the output signal and allowing to generate training data for sensors of various types.
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Markelov, N. "ANALYTICAL MODEL OF PACKET TRANSMISSION OF SPEECH AND DATA IN HF RADIO CHANNELS IN A COMPLEX SIGNAL-INTERFERENCE ENVIRONMENT." National Association of Scientists 1, no. 67 (June 15, 2021): 45–49. http://dx.doi.org/10.31618/nas.2413-5291.2021.1.67.422.
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The author has carried out an analytical simulation of the process of signal formation and processing in the HF channel during packet transmission of speech and data in a complex signal-interference environment. The totality of the result obtained can be the basis for the development of complex mathematical models of HF channels.
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Cai, Zhijun, Er-wei Bai, and Richard K. Shields. "Fatigue and non-fatigue mathematical muscle models during functional electrical stimulation of paralyzed muscle." Biomedical Signal Processing and Control 5, no. 2 (April 2010): 87–93. http://dx.doi.org/10.1016/j.bspc.2009.12.001.
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Merizalde, Yuri, Luis Hernández-Callejo, Oscar Duque-Perez, and Raúl Alberto López-Meraz. "Fault Detection of Wind Turbine Induction Generators through Current Signals and Various Signal Processing Techniques." Applied Sciences 10, no. 21 (October 22, 2020): 7389. http://dx.doi.org/10.3390/app10217389.
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In the wind industry (WI), a robust and effective maintenance system is essential. To minimize the maintenance cost, a large number of methodologies and mathematical models for predictive maintenance have been developed. Fault detection and diagnosis are carried out by processing and analyzing various types of signals, with the vibration signal predominating. In addition, most of the published proposals for wind turbine (WT) fault detection and diagnosis have used simulations and test benches. Based on previous work, this research report focuses on fault diagnosis, in this case using the electrical signal from an operating WT electric generator and applying various signal analysis and processing techniques to compare the effectiveness of each. The WT used for this research is 20 years old and works with a squirrel-cage induction generator (SCIG) which, according to the wind farm control systems, was fault-free. As a result, it has been possible to verify the feasibility of using the current signal to detect and diagnose faults through spectral analysis (SA) using a fast Fourier transform (FFT), periodogram, spectrogram, and scalogram.
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Gurnov, K. B., and E. M. Izotova. "Simulation of SAR signal processing system in telescopic mapping." Issues of radio electronics, no. 12 (February 3, 2021): 23–29. http://dx.doi.org/10.21778/2218-5453-2020-12-23-29.
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At the present stage of development of surveillance tools, the most popular are radar tools. A special place among such systems is occupied by radars with a synthesized antenna aperture, which make it possible to obtain high-resolution radar images with a relatively small size of the antenna system. The creation of such radar facilities has a number of features, which increases the cost of the development process and increases the time frame, and verification of work can be complicated by the inability to form the required conditions. To eliminate such difficulties, it is advisable to create adequate mathematical models of systems that would allow you to conduct all the necessary tests and work out algorithms, with minimal time spent. In this paper, a phenomenological model of the reflected signal in SAR is proposed, and a SAR model is developed that has a block structure and can be supplemented with modules to identify new dependencies.
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Kluth, Tobias. "Mathematical models for magnetic particle imaging." Inverse Problems 34, no. 8 (June 12, 2018): 083001. http://dx.doi.org/10.1088/1361-6420/aac535.
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Kovtun, S., A. Vetoshkin, A. Yermolenko, and V. Kutsenko. "CHARACTERISTICS OF THE IMPLICATIONS OF m-ROZPODL NAKAGAM." Наукові праці Державного науково-дослідного інституту випробувань і сертифікації озброєння та військової техніки 12, no. 3 (October 20, 2022): 43–54. http://dx.doi.org/10.37701/dndivsovt.13.2022.05.
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Detection of a correlation signal against the background of noise (occurence) is an important task of primary information processing in modern radio engineering systems of information transmission, control, navigation, radio monitoring and radiolocation. The reception of radio signals is accompanied by many accidental factors, which lead to the fact that the additive mixture very often has a non-causal distribution. For this reason, the methods of the theory of probability and mathematical statistics are used for the acceptance and processing of the accepted signal, and the acceptance and detection is regarded as a mathematical problem.
Receiving capabilities of radio engineering systems are largely determined by the detection characteristics, which, in turn, depend on the tightness with the received signal. In order to ensure the compliance, it is necessary to know the law of distribution of the intensity and probability of the output effect of the receiver. The knowledge of the distribution of the probability of frequency determines the characteristics of the detection of the receiver of radio engineering systems and provides a wide range of functional possibilities in the execution of statistical tasks in the primary processing of information.
Analytical expressions that determine the probability of correct detection through the probability of the hibnothreshold signal/noise ratio at the receiver output for coherent signals with a uniform initial phase and a nakagami-like amplitude are presented.
On the basis of the obtained analytical expressions a family of curves was created for signal models, where fluctuations are very small or absent in general and which are adequately described by Nakagami’s law of dispersion.
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Arik, Sercan O., Joseph M. Kahn, and Keang-Po Ho. "MIMO Signal Processing for Mode-Division Multiplexing: An overview of channel models and signal processing architectures." IEEE Signal Processing Magazine 31, no. 2 (March 2014): 25–34. http://dx.doi.org/10.1109/msp.2013.2290804.
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Mamalis, A. G., I. Nevliudov, and Yu Romashov. "An approach for numerical simulating and processing of measured electrical signals from board sensors installed on wheeled electro-mechanical platforms." Journal of Instrumentation 16, no. 10 (October 1, 2021): P10006. http://dx.doi.org/10.1088/1748-0221/16/10/p10006.
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Abstract The generalized approaches of mathematical modelling for numerical simulating and processing of measured electrical signals from board sensors installed on wheeled electro-mechanical platforms are developed in this research. The mathematical backgrounds of the developed approaches are elaborated on the basis of especially formulated initial-value problems need to be solved numerically or the identification procedure need to be applied. It is shown that using the Lagrange's formalism and the electro-mechanical analogies for constructing the improved coupled mathematical models both the mechanics and electrics and electronics of the wheeled platforms and the installed board sensors and the measuring electronic transducers allows having the more information if processing of the measured signals will be on the basis of such improved mathematical models. It is considered the particular example of using the proposed approaches dealt with simulating and processing the measured electric signals from the board accelerometer installed on the four wheeled electro-mechanic platform. Due to this example it was shown that using of the improved mathematical models allows the significantly wider possibilities of accelerometer measuring, so that the different parameters can be estimated by means processing the direct accelerometer measures using the corresponded mathematical models. It was shown that, the most difficulties of identification problems for processing the measured signals from the board sensors installed on the wheeled platforms are due to inherent them the mathematical incorrectness according to Hadamard. The effectiveness of using the filtering of the results of processing the measured signals is shown for the considered particular example of the identification problem also.
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Baranov, G., and R. Gabruk. "Simulator Software of Process Modeling of Radar Solution Under Action of Adaptive Detection of Target Objects in Conditions of Spacious Noise." Metrology and instruments, no. 4 (August 30, 2018): 51–55. http://dx.doi.org/10.33955/2307-2180(4)2018.51-55.
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In this paperare considered methods for optimizing spatio-temporal signal processing for the complete or partial suppression of unwanted side lobes of interference. The method of operation of the signal-filter pair was perfected using an iterative procedure to maximize the signal-to-noise ratio. Simulated verification of the developed technique was carried out. In order to train operators according to training programs, algebraic expressions are proposed. Mathematical models are implemented in Matlab programming environment.
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Li, Qiang. "Using Nonlinear Diffusion Model to Identify Music Signals." Advances in Mathematical Physics 2021 (October 13, 2021): 1–11. http://dx.doi.org/10.1155/2021/2210953.
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In this paper, combined with the partial differential equation music signal smoothing model, a new music signal recognition model is proposed. Experimental results show that this model has the advantages of the above two models at the same time, which can remove noise and enhance music signals. This paper also studies the music signal recognition method based on the nonlinear diffusion model. By distinguishing the flat area and the boundary area of the music signal, a new diffusion coefficient equation is obtained by combining these two methods, and the corresponding partial differential equation is discretized by the finite difference method with numerical solution. The application of partial differential equations in music signal processing is a relatively new topic. Because it can accurately model the music signal, it solves many complicated problems in music signal processing. Then, we use the group shift Fourier transform (GSFT) to transform this partial differential equation into a linear homogeneous differential equation system, and then use the series to obtain the solution of the linear homogeneous differential equation system, and finally use the group shift inverse Fourier transform to obtain the noise frequency modulation time-dependent solution of the probability density function of the interference signal. This paper attempts to use the mathematical method of stochastic differentiation to solve the key problem of the time-dependent solution of the probability density function of noise interference signals and to study the application of random differentiation theory in radar interference signal processing and music signal processing. At the end of the thesis, the application of stochastic differentiation in the filtering processing of music signals is tried. According to the inherent self-similarity of the music signal system and the completeness and stability of the empirical mode decomposition (EMD) algorithm, a new kind of EMD music using stochastic differentiation is proposed for signal filtering algorithm. This improved anisotropic diffusion method can maintain and enhance the boundary while smoothing the music signal. The filtering results of the actual music signal show that the algorithm is effective.
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Shlykov, Vladyslav, Vitalii Kotovskyi, Nikolaj Višniakov, and Andžela Šešok. "Model for Elimination of Mixed Noise from MRI Heart Images." Applied Sciences 10, no. 14 (July 9, 2020): 4747. http://dx.doi.org/10.3390/app10144747.
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A method for the preliminary processing of MRI images of the heart that allows for the elimination of fluctuation and impulse noise from useful signals is proposed. These types of noise are due to the regular geometric structure of the photoelectric elements of the MRI scanner matrix and the structure of the signal transmission channel. The aim of this work is to develop a comprehensive mathematical model for eliminating noise in the signal of an MRI scanner. In this work, mathematical models of linear and median filtering of impulse noise, fluctuation, and geometric noise are implemented. The mathematical models consist of the combined use of linear and median filters for recording MRI images of the heart. In the experiments, real MRI images of the heart from six patients with different diseases were used after noise was added to them. We were able to eliminate the impulse noise, geometric noise, and fluctuation noise in the MRI images by applying our filtering techniques. The filtering technique not only removed the noise, but also increased the contrast of the cancerous volumetric heterogeneous formations in the heart region.
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Kostyria, O., V. Storozhenko, and V. Naumenko. "Compensation of Multipath Interference in a Separated Passive Time and Frequency Synchronization Systems." Metrology and instruments, no. 4 (September 7, 2019): 17–23. http://dx.doi.org/10.33955/2307-2180(4)2019.17-23.
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Multipath propagation of radio waves negatively affects to the performance of telecommunications and radio navigation systems [1, 3]. When performing time and frequency synchronization tasks of spatially separated standards, the multipath signal propagation aggravates the probability of a correct synchronization and introduces an error. The presence of a multipath signal reduces the signal-to-noise ratio in the received signal, which in turn causes an increase in the synchronization error. The mathematical models of multipath interference suppression in the time and in the frequency domain are presented in the article. Compared to time processing, processing in the frequency domain reduces computational costs. The operation of suppression in the time domain has been verified experimentally.
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BOIKO, JULIY, ILYA PYATIN, and IGOR PARKHOMEY. "SIGNAL PROCESSING AND SYNCHRONIZATION TECHNIQUE IN SOFTWARE-DEFINED RADIO SYSTEMS WITH OFDM." Herald of Khmelnytskyi National University. Technical sciences 307, no. 2 (May 2, 2022): 123–32. http://dx.doi.org/10.31891/2307-5732-2022-307-2-123-132.
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The article describes modern concepts for the development of Software-defined Radio (SDR) technology. A functional diagram of a software-defined radio station using the method of transmitting information with modulation based on Orthogonal Frequency Division Multiplexing (OFDM) is proposed. The conditions for ensuring symbol synchronization of OFDM signals are investigated. It is determined that the disruption of the orthogonality of OFDM symbols is accompanied by such phenomena as the occurrence of inter-symbol interference and inter-channel interference. The method of constellation diagrams was used to study the effect of errors caused by interference on the quality of processing of multiposition signals. The effect of interference in a channel from OFDM on the phase of signals during their processing is estimated. Mathematical models of signals with OFDM in the presence of interference effects are obtained. Two types of errors are considered, which are caused by carrier distortion. In particular, the occurrence of phase noise is possible, the cause of which is associated with the instability of the generating equipment of the carrier signals both on the transmitting and on the receiving side. Another factor is carrier offset due to Doppler frequency. The proposed SDR receiver structure is based on the digital IF architecture. This architecture has more flexibility than traditional RF architectures and is not sensitive to DC offset, LO leakage, etc. Moreover, since the I/Q up/down conversion is done digitally in the IF stage, the negative effects caused by I/Q imbalance will be minimized. The SDR consists of a small piece of hardware at the RF input, i.e., an antenna and a high-rate ADC capable of capturing and digitizing broadband radio signals. To increase the communication range in SDR, we use amplifiers in front of two DAC/ADC stages. The receiver has a low-noise amplifier to reduce the quantization noise of the transducer and increase the Signal-to-noise Ratio (SNR). The data is then processed on specialized computational units within the embedded system, enabling important demodulation, synchronization, and decoding techniques to be implemented.
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Afonin, Igor L., Alexander L. Polyakov, Yury N. Tyschuk, Vladislav V. Golovin, and Gennady V. Slezkin. "Mathematical model for spacecrafts identification." Radioelectronics. Nanosystems. Information Technologies. 14, no. 2 (June 30, 2022): 111–18. http://dx.doi.org/10.17725/rensit.2022.14.111.
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Proposed below is a mathematical model for reception and processing of spurious (“uncontrolled” radiation) from constantly operating units of the special complex installed onboard a spacecraft. This model makes it possible to implement a new technique for identification of such radiation thus improving the capabilities of the space monitoring. At the same time creation of stand-alone radio systems solely for identification of the spacecrafts based on the proposed mathematic model would require significant expenses therefore it is worthwhile to add new identification hardware to the existing ground-based radio systems used for space flight control. Identifying features in the proposed mathematical model are the parameters of signals of the uncontrolled radiation from constantly operating units installed onboard spacecrafts that “leak” through antenna systems (master generators, heterodyne oscillators in the spacecraft radio receivers). Identification of spacecrafts by uncontrolled radiation from the receiving master generators and heterodyne oscillators involves keeping track of the behavior of oscillation parameters as well as identifying signs that distinguish the oscillations of one generator from another. Since the uncontrolled radiation from heterodyne oscillators is a harmonic oscillation, it features such parameters as amplitude, frequency and initial phase. It is impossible to use the amplitude and initial phase of the signal for identification purposes because the propagation medium strongly affects these parameters. The most informative for identification purposes is the frequency of oscillations, or rather, the behavior of the frequency changes over time. These changes are due to the frequency instability of the onboard master generators. The behavior of the frequency change depends on the characteristics of each onboard generator, which serves as a basis for identification. It should be noted that the identification process can be conditionally divided into two stages: the first stage includes validation of models and processing (evaluation) algorithms while the second stage involves classification of the results of processing (evaluation).
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Heister, Sergey R., and Thai T. Nguyn. "MATHEMATICAL MODELS OF THE RADAR SIGNAL REFLECTED FROM A HELICOPTER MAIN ROTOR IN APPLICATION TO INVERSE SYNTHESIS OF ANTENNA APERTURE." Journal of the Russian Universities. Radioelectronics 22, no. 3 (July 2, 2019): 74–87. http://dx.doi.org/10.32603/1993-8985-2019-22-3-74-87.
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Introduction. The basis for solving the problem of aircraft recognition is the formation of radar portraits, reflecting the constructive features of aerial vehicles. Portraits, which are radar images of the propellers of aerial vehicles, have high informativeness. These images allow us to distinguish the number and relative position of the propeller blades, as well as the direction of its rotation. The basis for obtaining such images are mathematical models of reflected signals. Objective. The aim of this paper is to develop mathematical models of the radar signal reflected from the helicopter main rotor applied to inverse synthetic aperture radar (ISAR). Methods and materials. ISAR processing is used to produce a radar image of a propeller in a radar with a monochromatic probing signal. The propeller blades in the models are approximated by different geometric shapes. The models used to describe the reflection from the propellers of helicopters and fixed-wing aircraft have significant differences. In the process of moving each blade of the helicopter main rotor makes characteristic movements (flapping, dragging, feathering), as well as bends in a vertical plane. Such movements and bendings of the blades are influence the phase of the signal reflected from the main rotor. It is necessary to take the phase change of the reflected signal into account as accurately as possible when developing an ISAR algorithm for imaging the main rotor. Results. We found that in the centimeter wavelength range the mathematical model of the signal reflected from the helicopter main rotor as a system of blades is most accurately described by representing each blade with a set of isotropic reflectors located on the main rotor’s blade leading and trailing edges. Taking into account the flapping movements and curved shapes of the blades in the model allows you to get as close as possible to the features of the real signal. Conclusion. The developed model which takes into account the flapping movements and bends of the helicopter main rotor blades can be used to improve the ISAR algorithms providing the radar imaging of aerial vehicles.
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Fokin, G. "MODELING OF THE PULSE SHAPING AND MATCHED FILTERS." Telecom IT 9, no. 2 (July 28, 2021): 77–94. http://dx.doi.org/10.31854/2307-1303-2021-9-2-77-94.
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Pulse shaping filtering on transmission and matched filtering on reception are one of the main stages of digital signal processing that directly affect the noise immunity of their reception, therefore, the models, developed in this work, are of certain methodological interest, the relevance of which is confirmed by continuing in the last years trend of implementing procedures for transmitting, receiving and processing signals by means of model-based design and software-defined radio. The presented work contains scripts for the synthesis of the pulse shaping and matched filters with given characteristics for the subsequent software implementation of simulation models for assessing the noise immunity of modern and future mobile communication and radio access systems. The formalization of the known mathematical models of intersymbol interference and the Nyquist filter for its elimination are accompanied by scripts in the Matlab environment for constructing and visualizing its impulse and frequency characteristics. The implemented software toolkit makes it possible to evaluate the influence of the smoothing coefficient and limiting the length of the impulse response, as well as to visualize the width of the signal spectrum in the frequency domain and its distortion by the eye diagram in the time domain.
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Kowalczyk, Adam, Anna Szlachta, Robert Hanus, and Rafał Chorzępa. "Estimation of Conditional Expected Value for Exponentially Autocorrelated Data." Metrology and Measurement Systems 24, no. 1 (March 1, 2017): 69–78. http://dx.doi.org/10.1515/mms-2017-0005.
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AbstractAutocorrelation of signals and measurement data makes it difficult to estimate their statistical characteristics. However, the scope of usefulness of autocorrelation functions for statistical description of signal relation is narrowed down to linear processing models. The use of the conditional expected value opens new possibilities in the description of interdependence of stochastic signals for linear and non-linear models. It is described with relatively simple mathematical models with corresponding simple algorithms of their practical implementation.The paper presents a practical model of exponential autocorrelation of measurement data and a theoretical analysis of its impact on the process of conditional averaging of data. Optimization conditions of the process were determined to decrease the variance of a characteristic of the conditional expected value. The obtained theoretical relations were compared with some examples of the experimental results.
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Pyayt, A. L., A. P. Kozionov, V. T. Kusherbaeva, I. I. Mokhov, V. V. Krzhizhanovskaya, B. J. Broekhuijsen, R. J. Meijer, and P. M. A. Sloot. "Signal analysis and anomaly detection for flood early warning systems." Journal of Hydroinformatics 16, no. 5 (March 21, 2014): 1025–43. http://dx.doi.org/10.2166/hydro.2014.067.
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We describe the detection methods and the results of anomalous conditions in dikes (earthen dams/levees) based on a simultaneous processing of several data streams originating from sensors installed in these dikes. Applied methods are especially valuable in cases where lack of information or computational resources prohibit computing the state of the dike with finite element and other mathematical models. The data-driven methods are part of the artificial intelligence (AI) component of the ‘Urbanflood’ early warning system. This AI component includes pre-processing (e.g., gap filling and measurements synchronization procedures) of data streams, feature extraction and anomaly detection by one-side (also known as one-class) classification methods. Our approach has been successfully validated during a non-destructive piping experiment at the Zeeland dike (The Netherlands).
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Berezovska, Yu V., and V. A. Vorob'ev. "The mathematical models of historical processes." Prikladnaya diskretnaya matematika, no. 16 (June 1, 2012): 105–25. http://dx.doi.org/10.17223/20710410/16/11.
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Staines, Anthony Spiteri. "Concurrency and Petri Net Models." International Journal of Circuits, Systems and Signal Processing 16 (March 11, 2022): 852–58. http://dx.doi.org/10.46300/9106.2022.16.104.
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Concurrency is a fundamental problem and a solution applicable to different areas of computing. Given the complexities and distribution of computer systems and services, concurrency is a modern area requiring proper attention. Petri nets are formalisms based on process representation both from a mathematical view and from a graphical or drawing like view. Petri nets are used to model concurrent processes. This work deals with understanding and representing low level concurrency in Petri nets, when this is not always visible and properly noted from the graphical structure. In this study an algebraic notation has been devised and is used to represent the Petri net structures. This algebraic notation is used as an alternative and simplified way of representation. The notation is explained and several simple examples are given. The notation presented can be used in conjunction with other Petri net analysis and verification methods. Some results and findings are discussed.
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Lainiotis, D. G., Paraskevas Papaparaskeva, and Kostas Plataniotis. "Nonlinear filtering for LIDAR signal processing." Mathematical Problems in Engineering 2, no. 5 (1996): 367–92. http://dx.doi.org/10.1155/s1024123x96000397.
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LIDAR (Laser Integrated Radar) is an engineering problem of great practical importance in environmental monitoring sciences. Signal processing for LIDAR applications involves highly nonlinear models and consequently nonlinear filtering. Optimal nonlinear filters, however, are practically unrealizable. In this paper, the Lainiotis's multi-model partitioning methodology and the related approximate but effective nonlinear filtering algorithms are reviewed and applied to LIDAR signal processing. Extensive simulation and performance evaluation of the multi-model partitioning approach and its application to LIDAR signal processing shows that the nonlinear partitioning methods are very effective and significantly superior to the nonlinear extended Kalman filter (EKF), which has been the standard nonlinear filter in past engineering applications.
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Volosyuk, Valeriy, and Semen Zhyla. "Statistical Theory of Optimal Stochastic Signals Processing in Multichannel Aerospace Imaging Radar Systems." Computation 10, no. 12 (December 18, 2022): 224. http://dx.doi.org/10.3390/computation10120224.
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The work is devoted to solving current scientific and applied problems of the development of radar imaging methods. These developments are based on statistical theory of optimal signal processing. These developments allow researchers to create coherent high-resolution information-enriched images as well as incoherent images. These methods can be practically applied in multichannel aerospace radars through the proposed programs and algorithms. Firstly, the following models of stochastic signals at the output of multichannel registration regions of scattered electro-magnetic fields, internal noise, and observation equations are developed and their statistical characteristics investigated. For the considered models of observation equations, the likelihood functional is defined. This definition is an important stage in optimizing spatial and temporal signal processing. These signals are distorted by internal receiver noises in radar systems. Secondly, by synthesising and analysing methods of measuring a radar cross section, the problem of incoherent imaging by aerospace radars with planar antenna array is solved. Thirdly, the obtained optimal mathematical operations are physically interpreted. The proposed interpretation helps to implement a quasi-optimal algorithm of radar cross section estimation in aerospace radar systems. Finally, to verify the proposed theory, a semi-natural experiment of real radio holograms processing was performed. These radio holograms are digital recordings of spatial and temporal signals by an airborne synthetic aperture radar (SAR) system. The results of the semi-natural experiment are presented and analysed in the paper. All the calculations, developments and results in this paper can be applied to new developments in areas such as remote sensing or non-destructive testing.
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Carin, Lawrence, Richard Baraniuk, Volkan Cevher, David Dunson, Michael Jordan, Guillermo Sapiro, and Michael Wakin. "Learning Low-Dimensional Signal Models." IEEE Signal Processing Magazine 28, no. 2 (March 2011): 39–51. http://dx.doi.org/10.1109/msp.2010.939733.
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Elliott, Terry, and Konstantinos Lagogiannis. "The Rise and Fall of Memory in a Model of Synaptic Integration." Neural Computation 24, no. 10 (October 2012): 2604–54. http://dx.doi.org/10.1162/neco_a_00335.
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Plasticity-inducing stimuli must typically be presented many times before synaptic plasticity is expressed, perhaps because induction signals gradually accumulate before overt strength changes occur. We consider memory dynamics in a mathematical model with synapses that integrate plasticity induction signals before expressing plasticity. We find that the memory trace initially rises before reaching a maximum and then falling. The memory signal dissociates into separate oblivescence and reminiscence components, with reminiscence initially dominating recall. In radical contrast, related but nonintegrative models exhibit only a highly problematic oblivescence. Synaptic integration mechanisms possess natural timescales, depending on the statistics of the induction signals. Together with neuromodulation, these timescales may therefore also begin to provide a natural account of the well-known spacing effect in the transition to late-phase plasticity. Finally, we propose experiments that could distinguish between integrative and nonintegrative synapses. Such experiments should further elucidate the synaptic signal processing mechanisms postulated by our model.
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Волосюк, Валерій Костянтинович, Володимир Володимирович Павліков, Семен Сергійович Жила, Едуард Олексійович Церне, Олексій Володимирович Одокієнко, Андрій Павлович Дьомін, Андрій Михайлович Гуменний, and Анатолій Владиславович Попов. "Алгоритм обробки сигналів для вертолітного широкосмугового шумового некогерентного радіовисотоміру." Aerospace technic and technology, no. 2 (April 25, 2022): 74–86. http://dx.doi.org/10.32620/aktt.2022.2.09.
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The algorithm for a helicopter or an unmanned aerial vehicle flight altitude measuring based on the processing of broadband and ultra-wideband pulsed stochastic signals has been synthesized for the first time by the maximum likelihood method. When formulating the initial data, mathematical models of the probing signal and the received observation are given, taking into account both various options for input path implementation, which impose restrictions on the observation equation form, and the geometry of the problem. When solving the problem, the statistical characteristics of the given models were found and studied. The calculated observation correlation function contains information about both the signal delay time and the radio pulse envelope, which makes it possible to obtain the algorithm for desired altitude parameter determining by one of two ways: differentiating the likelihood functional by the delay time or by the radio pulse envelope. At the same time, for the first time, the inversion equation for the statistical characteristics of the studied non-stationary processes in the frequency domain has been obtained. Such processes arise due to the presence of a radio pulse envelope. An important feature of the solved synthesis problem is a noise pulse transmitter use that implements the function of the underlying surface sounding, as well as taking into account the fact of the signal structure destruction during its radiation, propagation and reflection. Such a destruction of the signal shape doesn’t make it impossible to synthesize a radar with internal coherent processing algorithms when working on one receiving antenna and requires the search for other signal processing options. The use of a non-deterministic signal in the system also complicates the formalization of the delay time parameter in the likelihood function, since in this case the reference signal cannot be represented as a model or an analytical equation. Following the synthesized algorithm, a simulation model of a pulsed radar with a stochastic probing signal has developed and the results of its modeling are presented. The obtained output effect of the system fully corresponds to the classical theoretical calculations.
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LYAPIN, VICTOR, and MAKSIM SAMOKHVALOV. "STUDYING OF ELECTRICAL PARAMETERS OF PLANT AND SOIL OBJECTS AS ACTIVE-CAPACITIVE BIPOLAR." Elektrotekhnologii i elektrooborudovanie v APK 4, no. 41 (December 2020): 125–36. http://dx.doi.org/10.22314/2658-4859-2020-67-4-125-136.
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The key elements of the system for predicting electromagnetic damage are the electromagnetic source and the biological object. There is no complex of analytical models and programs for predicting damaging and critical conditions of electromagnetic impact on biological objects, as well as software components that implement developed mathematical models of real electromagnetic processes occurring in biological structures at different levels of the organization. (Research purpose) The research purpose is in developing a system for determining the electrical parameters of soil and biological objects (to develop ideas about the processes in the structures of different levels of organization of biological objects): in agricultural technologies for diagnostics of plant objects and soil; in laboratory conditions as a medium for creating and studying new electrical technologies, methods of analysis and processing of information signals. (Materials and methods) The method for monitoring electrical properties consists in applying a voltage with a constant and low-frequency component to a plant object, and simultaneously measuring the DC current, capacitive and resistive components of the low-frequency impedance. (Results and discussion) The proposed system for determining the electrical parameters of plant objects and soil allows to visualize the original signal; to perform calculation of informative parameters and statistical processing of the informative signal of a plant object and soil (construction of distribution laws, calculation of variance, mathematical expectation); to calculate the spectrum of the informative signal; to record the values of any of the specified informative parameters, both in real time and at the selected moment; to make time dependencies of informative parameters of plant objects and soil. (Conclusions) Authors implemented modes for measuring local DC resistance and monitoring the capacitive and resistive components in the area of electrical contact of two needles and other measuring electrodes with plant objects in the low-frequency range.
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Ferreira de Lima, Thomas, Alexander N. Tait, Armin Mehrabian, Mitchell A. Nahmias, Chaoran Huang, Hsuan-Tung Peng, Bicky A. Marquez, et al. "Primer on silicon neuromorphic photonic processors: architecture and compiler." Nanophotonics 9, no. 13 (August 10, 2020): 4055–73. http://dx.doi.org/10.1515/nanoph-2020-0172.
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AbstractMicroelectronic computers have encountered challenges in meeting all of today’s demands for information processing. Meeting these demands will require the development of unconventional computers employing alternative processing models and new device physics. Neural network models have come to dominate modern machine learning algorithms, and specialized electronic hardware has been developed to implement them more efficiently. A silicon photonic integration industry promises to bring manufacturing ecosystems normally reserved for microelectronics to photonics. Photonic devices have already found simple analog signal processing niches where electronics cannot provide sufficient bandwidth and reconfigurability. In order to solve more complex information processing problems, they will have to adopt a processing model that generalizes and scales. Neuromorphic photonics aims to map physical models of optoelectronic systems to abstract models of neural networks. It represents a new opportunity for machine information processing on sub-nanosecond timescales, with application to mathematical programming, intelligent radio frequency signal processing, and real-time control. The strategy of neuromorphic engineering is to externalize the risk of developing computational theory alongside hardware. The strategy of remaining compatible with silicon photonics externalizes the risk of platform development. In this perspective article, we provide a rationale for a neuromorphic photonics processor, envisioning its architecture and a compiler. We also discuss how it can be interfaced with a general purpose computer, i.e. a CPU, as a coprocessor to target specific applications. This paper is intended for a wide audience and provides a roadmap for expanding research in the direction of transforming neuromorphic photonics into a viable and useful candidate for accelerating neuromorphic computing.
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Hall, Peter. "On the amount of detail that can be recovered from a degraded signal." Advances in Applied Probability 19, no. 2 (June 1987): 371–95. http://dx.doi.org/10.2307/1427424.
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Motivated by applications in digital image processing, we discuss information-theoretic bounds to the amount of detail that can be recovered from a defocused, noisy signal. Mathematical models are constructed for test-pattern, defocusing and noise. Using these models, upper bounds are derived for the amount of detail that can be recovered from the degraded signal, using any method of image restoration. The bounds are used to assess the performance of the class of linear restorative procedures. Certain members of the class are shown to be optimal, in the sense that they attain the bounds, while others are shown to be sub-optimal. The effect of smoothness of point-spread function on the amount of resolvable detail is discussed concisely.
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Hall, Peter. "On the amount of detail that can be recovered from a degraded signal." Advances in Applied Probability 19, no. 02 (June 1987): 371–95. http://dx.doi.org/10.1017/s0001867800016591.
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Motivated by applications in digital image processing, we discuss information-theoretic bounds to the amount of detail that can be recovered from a defocused, noisy signal. Mathematical models are constructed for test-pattern, defocusing and noise. Using these models, upper bounds are derived for the amount of detail that can be recovered from the degraded signal, using any method of image restoration. The bounds are used to assess the performance of the class of linear restorative procedures. Certain members of the class are shown to be optimal, in the sense that they attain the bounds, while others are shown to be sub-optimal. The effect of smoothness of point-spread function on the amount of resolvable detail is discussed concisely.
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Tiuremnov, I. S., S. N. Ivanov, and A. S. Kraiushkin. "RESULTS OF EXPERIMENTAL STUDIES OF ACCELERATIONS OF THE DM-617 VIBRATORY ROLLER USING DIGITAL SIGNAL PROCESSING TECHNOLOGY." Russian Automobile and Highway Industry Journal 17, no. 2 (May 25, 2020): 182–95. http://dx.doi.org/10.26518/2071-7296-2020-17-2-182-195.
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Introduction. To improve the vibrating rollers in order to increase sealing capacity, reliability and vibration safety, the interaction of vibrating roller parts between each other and with compacted soil is simulated mathematically. The developed models are validated, i.e. compared with the results of experimental studies. However, the known results of experimental studies were obtained based on a relatively small list of vibrating roller models and soil types, as well as in a steady vibration mode. The paper presents the results of experimental studies, which used a vibratory drum of a roller to study its vertical vibration accelerations both in the steady vibration, as well as transient mode at turning the vibration generator on (speedup) and off (halt). This expands the range of opportunities to validate the existing and newly developed mathematical models.Materials and methods. Experimental studies of vertical vibration accelerations of a drum were conducted using the DM-617 vibrating roller when compacting natural sand-gravel aggregate. The accelerometer readings show high-frequency harmonics, which makes it significantly more difficult to determine amplitude values of vibration accelerations, therefore a low-frequency filter with a boundary frequency of 200 Hz was used for digital processing.Results. It was determined that when the DM-617 vibrating roller is compacting soil with maximum driving force within the range of variation of dynamic modulus of soil deformation Evd=14…25 MPа, amplitude values of vertical vibration accelerations of the vibratory drum are from 65... 77 to -61... -69 m/s2 . At the start-up (speedup) of vibration generator, acceleration amplitudes are 1.1 times higher than vertical accelerations of steady operation mode of the vibrating drum and practically do not depend on the dynamic modulus of soil deformation Evd. At turning off (stop) of the vibration generator, amplitude of vertical accelerations do not exceed the vertical accelerations of the steady operation mode of the vibratory drum.Discussion and conclusion. The vertical acceleration amplitudes of vibratory drums of DM-617 do not depend on the dynamic soil deformation modulus Evd, and this is consistent with the results of experimental studies of the vibratory drum mounted on DM-614. The obtained vertical vibration accelerations of the drum mounted on DM-617 in the steady vibration mode, as well as at switching the vibration generator on (speedup) and off (halt) make it possible to verify the existing and developed mathematical models of interaction of vibrating rollers with compacted soil.Financial transparency: the authors have no financial interest in the presented materials or methods. There is no conflict of interest.
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Morkun, Natalia, Iryna Zavsiehdashnia, Oleksandra Serdiuk, and Iryna Kasatkina. "Identification of models of nonlinear dynamic processes in mining on the basis of Volterra nuclei." E3S Web of Conferences 201 (2020): 01028. http://dx.doi.org/10.1051/e3sconf/202020101028.
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Solving the problem of improving efficiency of technological processes of mineral concentration is one of the essential for providing sustainability of mining enterprises. Currently, special attention is paid to optimization of technological processes in concentration of useful minerals. This approach calls for availability of high-quality data on the process, formation of corresponding databases and their subsequent processing to build adequate and efficient mathematical models of processes and systems. In order to improve quality of mathematical description of forming fractional characteristics of ore through applying technological aggregates in concentration, the authors suggest using power Volterra series that provide characteristics of a controlled object (its condition) as a sequence of multidimensional weight functions invariant to the type of an input signal – Volterra nuclei. Application of Volterra structures enables decreasing the modelling error to 0.039 under the root-mean-square error of 0.0594.
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Zhao, Zhizhen, Jong Chul Ye, and Yoram Bresler. "Generative Models for Inverse Imaging Problems: From mathematical foundations to physics-driven applications." IEEE Signal Processing Magazine 40, no. 1 (January 2023): 148–63. http://dx.doi.org/10.1109/msp.2022.3215282.
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Nikitchuk, T. M., T. A. Vakaliuk, O. V. Andreiev, O. L. Korenivska, V. V. Osadchyi, and M. G. Medvediev. "Mathematical model of the base unit of the biotechnical system as a type of edge devices." Journal of Physics: Conference Series 2288, no. 1 (June 1, 2022): 012004. http://dx.doi.org/10.1088/1742-6596/2288/1/012004.
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Abstract The rapid development of computer biometrics over the past 2-3 decades is largely due to the development and widespread introduction into clinical practice of new methods of studying the human body health, including pulse methods. It is possible to judge changes in hemodynamic characteristics, heart rate and blood flow rate in the studied part of the body based on the parameters of the pulse wave signal. At the same time, the physical processes of formation of the pulse wave shape have not been fully studied, although the number of biophysical models of blood circulation is quite significant. The development of such a model will allow to effectively apply modern developments in digital signal processing to the pulse wave and increase its diagnostic value. Qualitative model of pulse signal can be entrusted to the development of the base unit of the biotechnical system as a type of edge devices. The work is devoted to the improvement of methods of rapid diagnosis of the cardiovascular system based on the analysis of model pulsegrams. An adequate mathematical model of the pulse wave, which corresponds to real pulse signals in different states of the human body and contains mathematical relationships between the main parameters of pulsegrams, has been refined. The algorithm of express diagnostics with the established criteria of the analysis of pulsograms is offered.
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Suryakala, S. Vasanthadev, and Shanthi Prince. "Influence of data pre-processing techniques for plsr model to predict blood glucose by nir spectroscopy-=SUP=-*-=/SUP=-." Оптика и спектроскопия 130, no. 5 (2022): 773. http://dx.doi.org/10.21883/os.2022.05.52453.181-22.
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NIR diffuse reflectance spectroscopic spectra can be mathematically modelled to extract quantitative information by suitable multivariate calibration models. The analysis of spectral data becomes complex as the data is more prone to noise due to light scattering and baseline effects. These errors reduces the robustness and reliability of the developed calibration model. Hence data pre-processing becomes the most important aspect in data analysis. Different mathematical transformations are applied to remove the noise present in the data. This work focuses on the various empirical data pre-processing techniques like baseline correction, multiplicative scatter correction (MSC), robust MSC, extended multiplicative signal correction (EMSC), orthogonal signal correction (OSC) and (-log R) followed by standard normal variate (SNV) techniques for Partial Least Square Regression (PLSR) model in the prediction of blood glucose non-invasively. The performance of the PLSR model for the acquired (raw) spectral data and the same data subjected to different pre-processing techniques is analyzed. The model complexity and robustness is evaluated in terms of the number of latent variables (LVs) required to build the calibration model and obtained mean square prediction error after cross validation. This study utilizes the spectral data collected from 207 subjects from a diabetic center using Diffuse Reflectance Spectrometer (DRS). The analyzed results show that pre-processing based on (-log R) followed by SNV is found to perform well with reduced model complexity and minimum estimated mean square prediction error of 0.23 mg/dl among the other empirical pre-processing techniques. Keywords:
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Brezgunov, Oleksandr, and Sergey Brezgunov. "Calculation of the Amplitude and Initial Phase of the Signal from Its Most "Reliable" Fragments." PHYSICS OF ATMOSPHERE AND GEOSPACE 2, no. 1 (2021): 17–24. http://dx.doi.org/10.47774/phag.02.01.2021-2.
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The idea of improving the methods of processing the received radio signals used in radio communication and radiolocation systems is considered. It is proposed to consider the radio signal as a noise-resistant code with repetition of its periods (symbols), each of which carries the same information about the value of its amplitude and initial phase. The possibility of realization of coherent reception of radio signals with amplitude or biphasic discrete modulation under the influence of powerful noise on them by their most "reliable" (suitable for calculations) fragments, determined by the values of samples, received at moments when the amplitude of a received signal shall be equal to zero (samples correspond to the value of the noise component – point A) or be maximum – point E (the phase of signals shifted with respect to the phase of noise, by π/2 or 3π/4). The considered approach on processing of a mix of a signal and noise allows to define some varieties of "reliable" fragments (at difference of phases of noise and a signal on π/2 or 3π/4, at a match of zero values of signals and noise, at difference of phases of noise and a signal on the value smaller, than ±π/24) on values of samples in points A and E, and also to exclude from consideration fragments, decision on which often is erroneous. The possibility of obtaining an additional estimation ∆ of the quality of the decision on a fragment of a discrete signal (BPSK), with already calculated its average value SСР on the set of its fragments, which allows to select the best or several best fragments for the decision on the received signal is shown. Fragments with a difference of noise and signal phases on the value smaller than ±π/24 occur most often from all considered variants and allow to distinguish with high accuracy the initial phases of opposite signals (BPSK). To solve the problem, we used all possible temporal representations of fragments of signal, noise and a mixture of signal and noise, mathematical models and formulas of the theory of circuits and signals.