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Добірка наукової літератури з теми "Signal processing Mathematical models"

Автор: Grafiati

Опубліковано: 4 червня 2021

Оновлено: 25 січня 2023

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Статті в журналах з теми "Signal processing Mathematical models"

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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2

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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3

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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4

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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5

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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6

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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7

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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8

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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9

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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10

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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Дисертації з теми "Signal processing Mathematical models"

1

Fabrizio, Giuseppe Aureliano. "Space-time characterisation and adaptive processing of ionospherically-propagated HF signals /." Title page, table of contents and abstract only, 2000. http://web4.library.adelaide.edu.au/theses/09PH/09phf129.pdf.

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2

Cai, Qin. "Detecting Chaotic Signals with Nonlinear Models." PDXScholar, 1993. https://pdxscholar.library.pdx.edu/open_access_etds/4564.

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In this thesis we apply chaotic dynamic data analysis to the area of discrete time signal processing. A newly developed Hidden Filter Hidden Markov Model is introduced in detection of chaotic signals. Numerical experiments have verified that this novel nonlinear model outperforms linear AR model in detecting chaotic signals buried by noise having similar power spectra. A simple Histogram Model is proposed which can also be used to do detection on the data sets with chaotic behavior. Receiver Operating Characteristics for a variety of noise levels and model classes are reported.

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3

Webb, M. R. "Millimetre wave quasi-optical signal processing systems." Thesis, University of St Andrews, 1993. http://hdl.handle.net/10023/2827.

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The development of spatial signal processing techniques at millimetre wavelengths represents an area of science and technology that is new. At optical wavelengths, spatial signal processing techniques are well developed and are being applied to a variety of situations. In particular they are being used in pattern recognition systems with a great deal of success. At millimetre wavelengths, the kind of technology used for signal transport and processing is typically either waveguide based or quasi-optically based, or some hybrid of the two. It is the use of quasi-optical methods that opens up the possibility of applying some of the spatial signal processing techiques that up to the present time have almost exclusively been used at optical wavelengths. A generic device that opens up this dimension of spatial signal processing to millimetre wave quasi-optical systems is at the heart of the work described within this thesis. The device could be suitably called a millimetre wave quasi-optical spatial light modulator (8LM), and is identical in operation to the spatial light modulators used in many optical signal processing systems. Within this thesis both a theoretical and an experimental analysis of a specific millimetre wave quasi-optical spatial light modulator is undertaken. This thesis thus represents an attempt to open up this new area of research and development, and to establish for it, a helpful theoretical and experimental foundation. It is an area that involves a heterogeneous mix of various technologies, and it is an area that is full of potential. The development of the experimental method for measuring the beam patterns produced by millimetre wave quasi-optical spatial light modulators involved the separate development of two other components. Firstly, a sensitive, low-cost millimetre wave pyroelectric detector has been developed and characterised. And secondly, a high performance quasi-optical Faraday rotator (a polarisation rotator) has been developed and characterised. The polarisation state of a quasi-optical beam is the parameter most often exploited for signal processing applications in millimetre wave quasi-optical systems, and thus a high performance polarisation rotator has readily found many opportunities for use.

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4

Zhang, Zhiguo, and 張治國. "On bandwidth and scale selection in processing of time-varying signalswith applications." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2007. http://hub.hku.hk/bib/B39707465.

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5

Selén, Yngve. "Model selection /." Uppsala : Univ. : Dept. of Information Technology, Univ, 2004. http://www.it.uu.se/research/reports/lic/2004-003/.

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6

Stoffell, Kevin M. "Implementation of a Quadrature Mirror Filter Bank on an SRC reconfigurable computer for real-time signal processing." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2006. http://library.nps.navy.mil/uhtbin/hyperion/06Sep%5FStoffell.pdf.

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Thesis (M.S. in Electrical Engineering)--Naval Postgraduate School, September 2006.
Thesis Advisor(s): Douglas J. Fouts. "September 2006." Includes bibliographical references (p. 111-112). Also available in print.

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7

洪觀宇 and Roy Hung. "Time domain analysis and synthesis of cello tones based on perceptual quality and playing gestures." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1998. http://hub.hku.hk/bib/B31215348.

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8

Li, Xiao, and 李驍. "Channel estimation and timing synchronization in cooperative communication systems." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2009. http://hub.hku.hk/bib/B42841835.

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9

Sadeghi, Parastoo School of Electrical Engineering And Telecommunications UNSW. "Modelling, information capacity, and estimation of time-varying channels in mobile communication systems." Awarded by:University of New South Wales. School of Electrical Engineering And Telecommunications, 2006. http://handle.unsw.edu.au/1959.4/32310.

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In the first part of this thesis, the information capacity of time-varying fading channels is analysed using finite-state Markov channel (FSMC) models. Both fading channel amplitude and fading channel phase are modelled as finite-state Markov processes. The effect of the number of fading channel gain partitions on the capacity is studied (from 2 to 128 partitions). It is observed that the FSMC capacity is saturated when the number of fading channel gain partitions is larger than 4 to 8 times the number of channel input levels. The rapid FSMC capacity saturation with a small number of fading channel gain partitions can be used for the design of computationally simple receivers, with a negligible loss in the capacity. Furthermore, the effect of fading channel memory order on the capacity is studied (from first- to fourth-order). It is observed that low-order FSMC models can provide higher capacity estimates for fading channels than high-order FSMC models, especially when channel states are poorly observable in the presence of channel noise. To explain the effect of memory order on the FSMC capacity, the capacities of high-order and low-order FSMC models are analytically compared. It is shown that the capacity difference is caused by two factors: 1) the channel entropy difference, and 2) the channel observability difference between the high-order and low-order FSMC models. Due to the existence of the second factor, the capacity of high-order FSMC models can be lower than the capacity of low-order FSMC models. Two sufficient conditions are proven to predict when the low-order FSMC capacity is higher or lower than the high-order FSMC capacity. In the second part of this thesis, a new implicit (blind) channel estimation method in time- varying fading channels is proposed. The information source emits bits ???0??? and ???1??? with unequal probabilities. The unbalanced source distribution is used as a priori known signal structure at the receiver for channel estimation. Compared to pilot-symbol-assisted channel estimation, the proposed channel estimation technique can achieve a superior receiver bit error rate performance, especially at low signal to noise ratio conditions.

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10

Yang, Yang. "2D signal processing: efficient models for spectral compressive sensing & single image reflection suppression." Diss., University of Iowa, 2018. https://ir.uiowa.edu/etd/6667.

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Two efficient models in two-dimensional signal processing are proposed in the thesis. The first model deals with large scale spectral compressive sensing in continuous domain, which aims to recover a 2D spectrally sparse signal from partially observed time samples. The signal is assumed to be a superposition of s complex sinusoids. We propose a semidefinite program for the 2D signal recovery problem. Our model is able to handle large scale 2D signals of size 500*500, whereas traditional approaches only handle signals of size around 20*20. The second model deals with the problem of single image reflection suppression. Removing the undesired reflection from images taken through glass is of great importance in computer vision. It serves as a means to enhance the image quality for aesthetic purposes as well as to preprocess images in machine learning and pattern recognition applications. We propose a convex model to suppress the reflection from a single input image. Our model implies a partial differential equation with gradient thresholding, which is solved efficiently using Discrete Cosine Transform. Extensive experiments on synthetic and real-world images demonstrate that our approach achieves desirable reflection suppression results and dramatically reduces the execution time compared to the state of the art.

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Книги з теми "Signal processing Mathematical models"

1

Solo, Victor. Adaptive signal processing algorithms: Stability and performance. Englewood Cliffs, N.J: Prentice Hall, 1995.

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2

Signals and systems in biomedical engineering: Signal processing and physiological systems modeling. New York: Kluwer Academic/Plenum Publishers, 2000.

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3

Gromakov, I︠U︡ A. Optimalʹnai︠a︡ obrabotka radiosignalov bolʹshimi sistemami. Moskva: Ėko-Trendz, 2004.

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4

Statistical digital signal processing and modeling. New York: John Wiley & Sons, 1996.

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5

Numbers & notes: An introduction to musical signal processing. Portland, Ore: PSI Press, 2012.

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6

United States. Advanced Research Projects Agency., ed. An optical signal processing model for the interferometric fiber optic gyro. Santa Monica, CA: RAND, 1995.

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7

Hall, David L. Mathematical techniques in multisensor data fusion. Boston: Artech House, 1992.

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8

L, Hall David. Mathematical techniques in multisensor data fusion. Boston: Artech House, 1992.

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9

Signal processing for neuroscientists: Introduction to the analysis of physiological signals. Amsterdam: Elsevier/Academic Press, 2007.

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10

L, Hall David. Mathematical techniques in multi-sensor data fusion. 2nd ed. Boston: Artech House, 2004.

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Частини книг з теми "Signal processing Mathematical models"

1

Butler, John L., and Charles H. Sherman. "Mathematical Models for Acoustic Radiation." In Modern Acoustics and Signal Processing, 555–96. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-39044-4_11.

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2

Gamba, Jonah. "Radar Waveforms and Their Mathematical Models." In Radar Signal Processing for Autonomous Driving, 37–51. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9193-4_4.

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3

Abraham, Douglas A. "Mathematical Statistics." In Modern Acoustics and Signal Processing, 251–305. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-92983-5_5.

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4

Fuhrmann, Paul A., and Uwe Helmke. "On the Use of Functional Models in Model Reduction." In Perspectives in Mathematical System Theory, Control, and Signal Processing, 177–87. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-540-93918-4_16.

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5

Gopi, E. S. "Mathematical Model of Time Varying Wireless Channel Model." In Digital Signal Processing for Wireless Communication using Matlab, 55–92. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-82036-7_2.

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6

Brockett, Roger W. "Markov Models for Coherent Signals: Extrapolation in the Frequency Domain." In Perspectives in Mathematical System Theory, Control, and Signal Processing, 299–307. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-540-93918-4_27.

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Gopi, E. S. "Mathematical Model of the Time-Varying Wireless Channel." In Digital Signal Processing for Wireless Communication using Matlab, 1–50. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-20651-6_1.

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8

Stawiaski, Jean. "Optimal Path: Theory and Models for Vessel Segmentation." In Mathematical Morphology and Its Applications to Image and Signal Processing, 417–28. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21569-8_36.

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9

Jeulin, Dominique, and Pascal Laurenge. "Probabilistic Model of Rough Surfaces Obtained by Electro-Erosion." In Mathematical Morphology and its Applications to Image and Signal Processing, 289–96. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4613-0469-2_33.

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10

Yang, Lei, Liang Li, Chie Muraki Asano, and Akira Asano. "Primitive and Grain Estimation Using Flexible Magnification for a Morphological Texture Model." In Mathematical Morphology and Its Applications to Image and Signal Processing, 190–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21569-8_17.

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Тези доповідей конференцій з теми "Signal processing Mathematical models"

1

"Session MA7b Mathematical Models for Image Processing." In Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004. IEEE, 2004. http://dx.doi.org/10.1109/acssc.2004.1399104.

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2

Bouchoffra, D., and F. Ykhlef. "Mathematical models for machine learning and pattern recognition." In 2013 8th InternationalWorkshop on Systems, Signal Processing and their Applications (WoSSPA). IEEE, 2013. http://dx.doi.org/10.1109/wosspa.2013.6602331.

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3

Rohde, Steve M., William J. Williams, and Mitchell M. Rohde. "Application of Advanced Signal Processing Methods to Automotive Systems Testing." In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-59535.

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Анотація:

During the past twenty years there have been rapid developments in the creation and application of mathematical computer-based capabilities and tools (e.g., FEA) to simulate and synthesize vehicle systems. This has led to the concept of virtual product development. In parallel with the development of these tools, an equally sophisticated set of tools have been developed in the area of advanced signal processing. These tools, based upon mathematical and statistical modeling techniques, enable the extraction of useful information from data and have application throughout the entire vehicle creation process. Moreover, signal processing bridges the gap between the “virtual” and the “real” worlds — an extremely important concept that is changing the entire nature of what is thought of as “testing.” This paper discusses the use of advanced signal processing methods in vehicle creation with particular emphasis on its use in vehicle systems testing. Modern Time Frequency Analysis (TFA), a technique that was specifically designed to study transient signals and was in part pioneered by one of the authors (WJW), is highlighted. TFA expresses a signal jointly in time and frequency at very high resolution and as such can often provide profound insights. Applications of TFA to vehicle systems testing are presented related to Noise, Vibration, and Harshness (NVH) that enable sound quality analyses. For example, using TFA predictive models of consumer preferences for transient sounds that are useful to the automotive engineer in testing and modifying new vehicle subsystem designs are discussed. Other applications that are discussed deal with brake pedal feel, and characterizing vehicle crash signals. In the latter case TFA has resulted in some unique insights that were not provided by conventional statistical and mathematical analyses.

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4

Akman, Caglar, Okan Demir, and Tolga Sonmez. "Covid-19 SEIQR Spread Mathematical Model." In 2021 29th Signal Processing and Communications Applications Conference (SIU). IEEE, 2021. http://dx.doi.org/10.1109/siu53274.2021.9477975.

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5

Wu, Feilong, Wenjie Wang, Hui-Ming Wang, and Qinye Yin. "A unified mathematical model for spatial scrambling based secure wireless transmission and its wiretap method." In Signal Processing (WCSP 2011). IEEE, 2011. http://dx.doi.org/10.1109/wcsp.2011.6096860.

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6

Simsek, Mustafa, Ibrahim Delibalta, Lemi Baruh, and Suleyman S. Kozat. "Mathematical model of causal inference in Social Networks." In 2016 24th Signal Processing and Communication Application Conference (SIU). IEEE, 2016. http://dx.doi.org/10.1109/siu.2016.7495952.

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7

Analoui, Morteza, and Shahram Jamali. "TCP fairness enhancement through a mathematical parametric model." In Signal Processing with Special Track on Biomedical Engineering (CCSP). IEEE, 2005. http://dx.doi.org/10.1109/ccsp.2005.4977166.

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8

Artyushenko, Vladimir Mikhaylovich, and Vladimir Ivanovich Volovach. "The Mathematical Models of Transformation non-Gaussian Random Processes in the non-Linear non-Inertial Elements." In 2022 24th International Conference on Digital Signal Processing and its Applications (DSPA). IEEE, 2022. http://dx.doi.org/10.1109/dspa53304.2022.9790780.

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Moghaddam, Mohsen Ebrahimi. "A Mathematical Model to Estimate Out of Focus Blur." In 2007 5th International Symposium on Image and Signal Processing and Analysis. IEEE, 2007. http://dx.doi.org/10.1109/ispa.2007.4383705.

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"A STUDY OF STOCHASTIC RESONANCE AS A MATHEMATICAL MODEL OF ELECTROGASTROGRAM." In International Conference on Bio-inspired Systems and Signal Processing. SciTePress - Science and and Technology Publications, 2011. http://dx.doi.org/10.5220/0003159504500453.

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Звіти організацій з теми "Signal processing Mathematical models"

1

Luo, Zhi-Quan. Mathematical Analysis of Signal Processing Capabilities of Wireless Networks. Fort Belvoir, VA: Defense Technical Information Center, January 2009. http://dx.doi.org/10.21236/ada499991.

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2

Baraniuk, Richard G. Multiscale Statistical Models for Signal and Image Processing. Fort Belvoir, VA: Defense Technical Information Center, June 2004. http://dx.doi.org/10.21236/ada425177.

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3

Shubitidze, Fridon. A Complex Approach to UXO Discrimination: Combining Advanced EMI Forward Models and Statistical Signal Processing. Fort Belvoir, VA: Defense Technical Information Center, January 2012. http://dx.doi.org/10.21236/ada578937.

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4

Burnett, G. C. Damage Detection and Identification of Finite Element Models Using State-Space Based Signal Processing a Summation of Work Completed at the Lawrence Livermore National Laboratory February 1999 to April 2000. Office of Scientific and Technical Information (OSTI), April 2000. http://dx.doi.org/10.2172/793960.

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5

Tanny, Josef, Gabriel Katul, Shabtai Cohen, and Meir Teitel. Micrometeorological methods for inferring whole canopy evapotranspiration in large agricultural structures: measurements and modeling. United States Department of Agriculture, October 2015. http://dx.doi.org/10.32747/2015.7594402.bard.

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Original objectives and revisions The original objectives as stated in the approved proposal were: (1) To establish guidelines for the use of micrometeorological techniques as accurate, reliable and low-cost tools for continuous monitoring of whole canopy ET of common crops grown in large agricultural structures. (2) To adapt existing methods for protected cultivation environments. (3) To combine previously derived theoretical models of air flow and scalar fluxes in large agricultural structures (an outcome of our previous BARD project) with ET data derived from application of turbulent transport techniques for different crops and structure types. All the objectives have been successfully addressed. The study was focused on both screenhouses and naturally ventilated greenhouses, and all proposed methods were examined. Background to the topic Our previous BARD project established that the eddy covariance (EC) technique is suitable for whole canopy evapotranspiration measurements in large agricultural screenhouses. Nevertheless, the eddy covariance technique remains difficult to apply in the farm due to costs, operational complexity, and post-processing of data – thereby inviting alternative techniques to be developed. The subject of this project was: 1) the evaluation of four turbulent transport (TT) techniques, namely, Surface Renewal (SR), Flux-Variance (FV), Half-order Time Derivative (HTD) and Bowen Ratio (BR), whose instrumentation needs and operational demands are not as elaborate as the EC, to estimate evapotranspiration within large agricultural structures; and 2) the development of mathematical models able to predict water savings and account for the external environmental conditions, physiological properties of the plant, and structure properties as well as to evaluate the necessary micrometeorological conditions for utilizing the above turbulent transfer methods in such protected environments. Major conclusions and achievements The major conclusions are: (i) the SR and FV techniques were suitable for reliable estimates of ET in shading and insect-proof screenhouses; (ii) The BR technique was reliable in shading screenhouses; (iii) HTD provided reasonable results in the shading and insect proof screenhouses; (iv) Quality control analysis of the EC method showed that conditions in the shading and insect proof screenhouses were reasonable for flux measurements. However, in the plastic covered greenhouse energy balance closure was poor. Therefore, the alternative methods could not be analyzed in the greenhouse; (v) A multi-layered flux footprint model was developed for a ‘generic’ crop canopy situated within a protected environment such as a large screenhouse. The new model accounts for the vertically distributed sources and sinks within the canopy volume as well as for modifications introduced by the screen on the flow field and microenvironment. The effect of the screen on fetch as a function of its relative height above the canopy is then studied for the first time and compared to the case where the screen is absent. The model calculations agreed with field experiments based on EC measurements from two screenhouse experiments. Implications, both scientific and agricultural The study established for the first time, both experimentally and theoretically, the use of four simple TT techniques for ET estimates within large agricultural screenhouses. Such measurements, along with reliable theoretical models, will enable the future development of lowcost ET monitoring system which will be attainable for day-to-day use by growers in improving irrigation management.

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Modlo, Yevhenii O., Serhiy O. Semerikov, Stanislav L. Bondarevskyi, Stanislav T. Tolmachev, Oksana M. Markova, and Pavlo P. Nechypurenko. Methods of using mobile Internet devices in the formation of the general scientific component of bachelor in electromechanics competency in modeling of technical objects. [б. в.], February 2020. http://dx.doi.org/10.31812/123456789/3677.

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An analysis of the experience of professional training bachelors of electromechanics in Ukraine and abroad made it possible to determine that one of the leading trends in its modernization is the synergistic integration of various engineering branches (mechanical, electrical, electronic engineering and automation) in mechatronics for the purpose of design, manufacture, operation and maintenance electromechanical equipment. Teaching mechatronics provides for the meaningful integration of various disciplines of professional and practical training bachelors of electromechanics based on the concept of modeling and technological integration of various organizational forms and teaching methods based on the concept of mobility. Within this approach, the leading learning tools of bachelors of electromechanics are mobile Internet devices (MID) – a multimedia mobile devices that provide wireless access to information and communication Internet services for collecting, organizing, storing, processing, transmitting, presenting all kinds of messages and data. The authors reveals the main possibilities of using MID in learning to ensure equal access to education, personalized learning, instant feedback and evaluating learning outcomes, mobile learning, productive use of time spent in classrooms, creating mobile learning communities, support situated learning, development of continuous seamless learning, ensuring the gap between formal and informal learning, minimize educational disruption in conflict and disaster areas, assist learners with disabilities, improve the quality of the communication and the management of institution, and maximize the cost-efficiency. Bachelor of electromechanics competency in modeling of technical objects is a personal and vocational ability, which includes a system of knowledge, skills, experience in learning and research activities on modeling mechatronic systems and a positive value attitude towards it; bachelor of electromechanics should be ready and able to use methods and software/hardware modeling tools for processes analyzes, systems synthesis, evaluating their reliability and effectiveness for solving practical problems in professional field. The competency structure of the bachelor of electromechanics in the modeling of technical objects is reflected in three groups of competencies: general scientific, general professional and specialized professional. The implementation of the technique of using MID in learning bachelors of electromechanics in modeling of technical objects is the appropriate methodic of using, the component of which is partial methods for using MID in the formation of the general scientific component of the bachelor of electromechanics competency in modeling of technical objects, are disclosed by example academic disciplines “Higher mathematics”, “Computers and programming”, “Engineering mechanics”, “Electrical machines”. The leading tools of formation of the general scientific component of bachelor in electromechanics competency in modeling of technical objects are augmented reality mobile tools (to visualize the objects’ structure and modeling results), mobile computer mathematical systems (universal tools used at all stages of modeling learning), cloud based spreadsheets (as modeling tools) and text editors (to make the program description of model), mobile computer-aided design systems (to create and view the physical properties of models of technical objects) and mobile communication tools (to organize a joint activity in modeling).

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7

Alchanatis, Victor, Stephen W. Searcy, Moshe Meron, W. Lee, G. Y. Li, and A. Ben Porath. Prediction of Nitrogen Stress Using Reflectance Techniques. United States Department of Agriculture, November 2001. http://dx.doi.org/10.32747/2001.7580664.bard.

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Commercial agriculture has come under increasing pressure to reduce nitrogen fertilizer inputs in order to minimize potential nonpoint source pollution of ground and surface waters. This has resulted in increased interest in site specific fertilizer management. One way to solve pollution problems would be to determine crop nutrient needs in real time, using remote detection, and regulating fertilizer dispensed by an applicator. By detecting actual plant needs, only the additional nitrogen necessary to optimize production would be supplied. This research aimed to develop techniques for real time assessment of nitrogen status of corn using a mobile sensor with the potential to regulate nitrogen application based on data from that sensor. Specifically, the research first attempted to determine the system parameters necessary to optimize reflectance spectra of corn plants as a function of growth stage, chlorophyll and nitrogen status. In addition to that, an adaptable, multispectral sensor and the signal processing algorithm to provide real time, in-field assessment of corn nitrogen status was developed. Spectral characteristics of corn leaves reflectance were investigated in order to estimate the nitrogen status of the plants, using a commercial laboratory spectrometer. Statistical models relating leaf N and reflectance spectra were developed for both greenhouse and field plots. A basis was established for assessing nitrogen status using spectral reflectance from plant canopies. The combined effect of variety and N treatment was studied by measuring the reflectance of three varieties of different leaf characteristic color and five different N treatments. The variety effect on the reflectance at 552 nm was not significant (a = 0.01), while canonical discriminant analysis showed promising results for distinguishing different variety and N treatment, using spectral reflectance. Ambient illumination was found inappropriate for reliable, one-beam spectral reflectance measurement of the plants canopy due to the strong spectral lines of sunlight. Therefore, artificial light was consequently used. For in-field N status measurement, a dark chamber was constructed, to include the sensor, along with artificial illumination. Two different approaches were tested (i) use of spatially scattered artificial light, and (ii) use of collimated artificial light beam. It was found that the collimated beam along with a proper design of the sensor-beam geometry yielded the best results in terms of reducing the noise due to variable background, and maintaining the same distance from the sensor to the sample point of the canopy. A multispectral sensor assembly, based on a linear variable filter was designed, constructed and tested. The sensor assembly combined two sensors to cover the range of 400 to 1100 nm, a mounting frame, and a field data acquisition system. Using the mobile dark chamber and the developed sensor, as well as an off-the-shelf sensor, in- field nitrogen status of the plants canopy was measured. Statistical analysis of the acquired in-field data showed that the nitrogen status of the com leaves can be predicted with a SEP (Standard Error of Prediction) of 0.27%. The stage of maturity of the crop affected the relationship between the reflectance spectrum and the nitrogen status of the leaves. Specifically, the best prediction results were obtained when a separate model was used for each maturity stage. In-field assessment of the nitrogen status of corn leaves was successfully carried out by non contact measurement of the reflectance spectrum. This technology is now mature to be incorporated in field implements for on-line control of fertilizer application.

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