Journal articles on the topic 'Statistical and digital signal processing'
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Gruber, Marvin H. J. "Statistical Digital Signal Processing and Modeling." Technometrics 39, no. 3 (August 1997): 335–36. http://dx.doi.org/10.1080/00401706.1997.10485128.
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Istomin, Andrey, and Egor Demidchenko. "DIGITAL PROCESSING OF THE ELECTROMYOGRAM SIGNAL." Modern Technologies and Scientific and Technological Progress 2020, no. 1 (June 16, 2020): 111–12. http://dx.doi.org/10.36629/2686-9896-2020-1-111-112.
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As a result of the study of physiological processes occurring in the human hand, data were obtained that are subject to analysis and statistical processing in the environment for solving engineering and scientific problems of Matlab
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Sala-Alvarez, J., and G. Vazquez-Grau. "Statistical reference criteria for adaptive signal processing in digital communications." IEEE Transactions on Signal Processing 45, no. 1 (1997): 14–31. http://dx.doi.org/10.1109/78.552202.
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Qi, Yang, Taichu Shi, and Ben Wu. "Wideband Mixed Signal Separation Based on Photonic Signal Processing." Telecom 2, no. 4 (November 2, 2021): 413–29. http://dx.doi.org/10.3390/telecom2040024.
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The growing needs for high-speed and secure communications create an increasing challenge to the contemporary framework of signal processing. The coexistence of multiple high-speed wireless communication systems generates wideband interference. To protect the security and especially the privacy of users’ communications requires stealth communication that hides and recovers private information against eavesdropping attacks. The major problem in interference management and stealth information recovery is to separate the signal of interest from wideband interference/noise. However, the increasing signal bandwidth presents a real challenge to existing capabilities in separating the mixed signal and results in unacceptable latency. The photonic circuit processes a signal in an analog way with a unanimous frequency response over GHz bandwidth. The digital processor measures the statistical patterns of the signals with sampling rate orders of magnitude smaller than the Nyquist frequency. Under-sampling the signals significantly reduces the workload of the digital processor while providing accurate control of the photonic circuit to perform the real-time signal separations. The wideband mixed signal separation, based on photonic signal processing is scalable to multiple stages with the performance of each stage accrued.
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A.O., Bello, and Kabari L.G. "Digital Signal Processing for Predicting Stock Prices." British Journal of Computer, Networking and Information Technology 4, no. 2 (September 5, 2021): 12–21. http://dx.doi.org/10.52589/bjcnit-xnp3ubpl.
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With the exponential growth of big data and data warehousing, the amount of data collected from various stock markets around the world has increased significantly. It is now impossible to process and analyze data using mathematical techniques and basic statistical calculations to forecast trends such as closing and opening prices, as well as daily stock market lows and highs. The development of smart and automated stock market forecasting systems has made significant progress in recent years. Digital signal processing is required for analysis and preprocessing because of the accuracy and speed with which these large amounts of data must be processed and analyzed. In this paper, we evaluate some of these predictive algorithms based on three parameters such as speed, accuracy and complexity, we analyze the data using the dataset from kaggle.com and we implement these algorithms using pythons. The results of our analysis in this paper shows a significant correlation between the yearly prices until the year 2018 where there is a significant increase in stock price.
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Karachun, V. Ya. "Digital signal processing using Schauder functions." Journal of Mathematical Sciences 71, no. 4 (September 1994): 2599–601. http://dx.doi.org/10.1007/bf02111964.
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Dempster, A. G., and M. D. Macleod. "Variable statistical wordlength in digital filters." IEE Proceedings - Vision, Image, and Signal Processing 143, no. 1 (1996): 62. http://dx.doi.org/10.1049/ip-vis:19960256.
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Tulyakova, N. O., and O. M. Trofymchuk. "Modified algorithms for signal nonlinear trend detection." Radiotekhnika, no. 206 (September 24, 2021): 137–51. http://dx.doi.org/10.30837/rt.2021.3.206.13.
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There is a problem of nonlinear (abrupt) signal trend detection in many digital signals processing practical applications. In particular, in the field of biomedical signals processing, the actual task is the elimination of abrupt signal baseline distortions caused by the patient's movements. For processing such signals containing edges and other discontinues, linear filtering based on discrete Fourier or cosine transforms leads to significant smoothing of a signal. Median type algorithms related to nonlinear stable (robust) filters are successfully applied for filtering such signals, in particular, high efficiency is provided by median hybrid filters with finite impulse response (FIR). The article considers simple algorithms of the class of FIR-median hybrid filters used for signal nonlinear trend detection. It is proposed to modify these algorithms by replacing the operation of finding the median of the data in the sliding filter window with the calculation of their myriad, as well as adding weights (number of duplications) to certain window elements. Statistical estimates of filter efficiency according to the mean square error (MSE) criterion for test signals like “step” and “ramp” edges, and triangular peak and parabola have been obtained. The high efficiency of the investigated nonlinear filters for the listed test signals types and the improvements achieved as a result of the proposed filter modifications are shown based on the analysis of the filter output signals and statistical estimates of their quality. Some examples of processing biomedical signals of electroencephalograms which illustrate good quality of noise suppression and signal abrupt changes preservation, and motion artifacts removal without large signal distortions are given.
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Глушков, А. Н., Ю. В. Литвиненко, Б. Н. Тишуков, and Е. В. Черноярова. "DIGITAL SIGNAL DEMODULATOR WITH AMPLITUDE-PHASE MANIPULATION." ВЕСТНИК ВОРОНЕЖСКОГО ГОСУДАРСТВЕННОГО ТЕХНИЧЕСКОГО УНИВЕРСИТЕТА 19, no. 5 (November 7, 2023): 115–20. http://dx.doi.org/10.36622/vstu.2023.19.5.016.
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исследуется оптимальный цифровой алгоритм когерентной демодуляции сигналов с амплитудно-фазовой манипуляцией (АФМ или APSK). Демодуляция фазы выполняется на основе фазового детектора сигналов с многопозиционной фазовой манипуляцией, а амплитуды символов определяются по откликам квадратурных каналов обработки сигнала. Проведен анализ алгоритма обработки сигнала с АФМ, рассмотрены временные реализации откликов демодулятора. Определена помехоустойчивость демодуляции для сигналов с двухуровневой АФМ для двух наиболее распространенных вариантов созвездий, оценены вероятности ошибочной демодуляции фазы и амплитуды сигнала, дан сравнительный анализ помехоустойчивости сигналов с различными созвездиями. Рассмотрена помехоустойчивость демодуляции сигналов с амплитудной относительно-фазовой манипуляцией (АОФМ), дан сравнительный анализ потерь в отношении сигнал/шум по сравнению с АФМ для различных вариантов созвездий. Проведено статистическое имитационное моделирование алгоритма демодуляции при воздействии шумовой помехи. Исследовано влияние на помехоустойчивость погрешностей оценки пороговых уровней принимаемых сигналов. Реализация демодулятора ориентирована на программируемые логические интегральные схемы (ПЛИС) the optimal digital algorithm for coherent demodulation of signals with amplitude-phase modulation (APSK) is investigated. Phase demodulation is performed on the basis of a phase detector of signals with multi-position phase manipulation, and the amplitudes of symbols are determined by the responses of quadrature signal processing channels. The analysis of the algorithm of signal processing with APSK is carried out, the time realizations of the responses of the de-modulator are considered. The noise immunity of demodulation for signals with a two-level APSK for the two most common variants of constellations is determined, the probabilities of erroneous demodulation of the phase and amplitude of the signal are estimated, a comparative analysis of the noise immunity of signals with different constellations is given. The noise immunity of demodulation of signals with amplitude relative-phase manipulation (ARFM) is considered, a comparative analysis of signal-to-noise losses in comparison with APSK for various constellation variations is given. Statistical simulation of the demodulation algorithm under the influence of noise interference is carried out. The influence of errors in the estimation of threshold levels of the received signals on the noise immunity is investigated. The implementation of the demodulator is focused on programmable logic integrated circuits (FPGAs)
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Semenishchev, Evgenii, Igor Shraifel, and Ilya Svirin. "Two approaches to solving the problem of smoothing digital signals based on a combined criterion." Serbian Journal of Electrical Engineering 14, no. 3 (2017): 365–77. http://dx.doi.org/10.2298/sjee1703365s.
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The paper presents a method for smoothing signals represented by a single realization of a finite-length random process, under conditions of a limited amount of a priori information about the signal function and statistical characteristics the noise component. The recommendations on the use of parameters affecting the processing speed and the efficiency of smoothing are given. Two solutions are presented to obtain the result of smoothing the signals. The efficiency results are shown for the processing of digital signals. Examples of comparison of simple methods and suggested ones are given.
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Bruce, Lori Mann, Navaneethakrishnan Balraj, Yunlong Zhang, and Qingyong Yu. "Automated Accident Detection in Intersections via Digital Audio Signal Processing." Transportation Research Record: Journal of the Transportation Research Board 1840, no. 1 (January 2003): 186–92. http://dx.doi.org/10.3141/1840-21.
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A system for automated traffic accident detection in intersections was designed. The input to the system is a 3-s segment of audio signal. The system can be operated in two modes: the two-class and multiclass modes. The output of the two-class mode is a label of “crash” or “noncrash.” In the multiclass mode of operation, the system identifies crashes as well as several types of noncrash incidents, including normal traffic and construction sounds. The system is composed of three main signal processing stages: feature extraction, feature reduction, and classification. Five methods of feature extraction were investigated and compared; these are based on the discrete wavelet transform, fast Fourier transform, discrete cosine transform, real cepstral transform, and mel frequency cepstral transform. Statistical methods are used for feature optimization and classification. Three types of classifiers are investigated and compared; these are the nearest-mean, maximum-likelihood, and nearest-neighbor methods. The results of the study show that the optimum design uses wavelet-based features in combination with the maximum-likelihood classifier. The system is computationally inexpensive relative to the other methods investigated, and the system consistently results in accident detection accuracies of 95% to 100% when the audio signal has a signal-to-noise-ratio of at least 0 decibels.
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Sadovskiy, I. S., Y. Y. Bobkov, and I. Y. Malevich. "Prototype of Mobile Meter Waveband Radar with Improved Functionality." Doklady BGUIR 20, no. 2 (April 5, 2022): 71–77. http://dx.doi.org/10.35596/1729-7648-2022-20-2-71-77.
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Actual stage of meter waveband radar evolution is the design of mobile radar with improved surveillance functions, as well as signal generation and processing. Such radars measure coordinates of aircraft in 3D space with adaptive change of operation frequency, parameters of probing signal, and polarization. Except radiolocation tasks, such radars allow to carry out integral information processing, EM analysis, ELINT, as well as jamming and clutter canceling, and must have height mobility and secrecy properties. The achievement of these properties is possible due to the application of digital antenna arrays with digital solid-state Tx/Rx modules, modular construction of all radar subsystems, digital beamforming technology, adoptive algorithms of space-time, and statistical processing of received signals. The prototype of meter-wavelength band radar system with height effectivity and informativity of radiolocation receiving, with the capability of fast moving and deploying is review in this article. The proposed radar system allows to provide measuring coordinates of an aircraft in 3D space, large distance detection, tracking and targeting of all types of aircrafts (including stealth aircrafts), carry out integral processing of radiolocation information, ELINT, EM analysis, as well as jamming and clatter canceling.
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Shlezinger, Nir, and Yonina C. Eldar. "Deep Task-Based Quantization." Entropy 23, no. 1 (January 13, 2021): 104. http://dx.doi.org/10.3390/e23010104.
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Quantizers play a critical role in digital signal processing systems. Recent works have shown that the performance of acquiring multiple analog signals using scalar analog-to-digital converters (ADCs) can be significantly improved by processing the signals prior to quantization. However, the design of such hybrid quantizers is quite complex, and their implementation requires complete knowledge of the statistical model of the analog signal. In this work we design data-driven task-oriented quantization systems with scalar ADCs, which determine their analog-to-digital mapping using deep learning tools. These mappings are designed to facilitate the task of recovering underlying information from the quantized signals. By using deep learning, we circumvent the need to explicitly recover the system model and to find the proper quantization rule for it. Our main target application is multiple-input multiple-output (MIMO) communication receivers, which simultaneously acquire a set of analog signals, and are commonly subject to constraints on the number of bits. Our results indicate that, in a MIMO channel estimation setup, the proposed deep task-bask quantizer is capable of approaching the optimal performance limits dictated by indirect rate-distortion theory, achievable using vector quantizers and requiring complete knowledge of the underlying statistical model. Furthermore, for a symbol detection scenario, it is demonstrated that the proposed approach can realize reliable bit-efficient hybrid MIMO receivers capable of setting their quantization rule in light of the task.
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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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Hall, Peter, J. W. Kay, and D. M. Titterington. "On estimation of noise variance in two-dimensional signal processing." Advances in Applied Probability 23, no. 3 (September 1991): 476–95. http://dx.doi.org/10.2307/1427618.
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Estimation of noise variance is an important component of digital signal processing, in particular of image processing. In this paper we develop methods for estimating the variance of white noise in a two-dimensional degraded signal. We discuss optimal configurations of pixels for difference-based estimation, and describe asymptotically optimal selection of weights for the component pixels. After extensive analysis of possible configurations we recommend averaging linear configurations over a variety of different orientations (usually two or four). This approach produces estimators with properties of both statistical and numerical efficiency.
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Hall, Peter, J. W. Kay, and D. M. Titterington. "On estimation of noise variance in two-dimensional signal processing." Advances in Applied Probability 23, no. 03 (September 1991): 476–95. http://dx.doi.org/10.1017/s0001867800023697.
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Estimation of noise variance is an important component of digital signal processing, in particular of image processing. In this paper we develop methods for estimating the variance of white noise in a two-dimensional degraded signal. We discuss optimal configurations of pixels for difference-based estimation, and describe asymptotically optimal selection of weights for the component pixels. After extensive analysis of possible configurations we recommend averaging linear configurations over a variety of different orientations (usually two or four). This approach produces estimators with properties of both statistical and numerical efficiency.
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Sarkar, Mrinmoy, Dhiman Chowdhury, Celia Shahnaz, and Shaikh Anowarul Fattah. "Application of Electrical Network Frequency of Digital Recordings for Location-Stamp Verification." Applied Sciences 9, no. 15 (August 2, 2019): 3135. http://dx.doi.org/10.3390/app9153135.
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Electrical network frequency (ENF) is a signature of a power distribution grid. It represents the deviation from the nominal frequency (50 or 60 Hz) of a power system network. The variations in ENF sequences within a grid are subject to load fluctuations within that particular grid. These ENF variations are inherently located in a multimedia signal, which is recorded close to the grid or directly from the mains power line. Thus, the specific location of a recording can be identified by analyzing the ENF sequences of the multimedia signal in absence of the concurrent power signal. In this article, a novel approach to location-stamp authentication based on ENF sequences of digital recordings is presented. ENF patterns are extracted from a number of power and audio signals recorded in different grid locations across the world. The extracted ENF signals are decomposed into low outliers and high outliers frequency segments and potential feature vectors are determined for these ENF segments by statistical and signal processing analysis. Then, a multi-class support vector machine (SVM) classification model is developed to verify the location-stamp information of the recordings. The performance evaluations corroborate the efficacy of the proposed framework.
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Lesnykh, A. A., and I. A. Shirokov. "Designing a digital-signal-processing extension for multipurpose microprocessors." Journal of Mathematical Sciences 152, no. 2 (July 2008): 247–62. http://dx.doi.org/10.1007/s10958-008-9058-7.
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Zaitsev, Dmitry, Vitaliy Bryksin, Konstantin Belotelov, Yulia Kompaniets, and Roman Iakovlev. "Algorithms and Measuring Complex for Classification of Seismic Signal Sources, Determination of Distance and Azimuth to the Point of Excitation of Surface Waves." Informatics and Automation 21, no. 6 (November 24, 2022): 1211–39. http://dx.doi.org/10.15622/ia.21.6.5.
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Machine learning and digital signal processing methods are used in various industries, including in the analysis and classification of seismic signals from surface sources. The developed wave type analysis algorithm makes it possible to automatically identify and, accordingly, separate incoming seismic waves based on their characteristics. To distinguish the types of waves, a seismic measuring complex is used that determines the characteristics of the boundary waves of surface sources using special molecular electronic sensors of angular and linear oscillations. The results of the algorithm for processing data obtained by the method of seismic observations using spectral analysis based on the Morlet wavelet are presented. The paper also describes an algorithm for classifying signal sources, determining the distance and azimuth to the point of excitation of surface waves, considers the use of statistical characteristics and MFCC (Mel-frequency cepstral coefficients) parameters, as well as their joint application. At the same time, the following were used as statistical characteristics of the signal: variance, kurtosis coefficient, entropy and average value, and gradient boosting was chosen as a machine learning method; a machine learning method based on gradient boosting using statistical and MFCC parameters was used as a method for determining the distance to the signal source. The training was conducted on test data based on the selected special parameters of signals from sources of seismic excitation of surface waves. From a practical point of view, new methods of seismic observations and analysis of boundary waves make it possible to solve the problem of ensuring a dense arrangement of sensors in hard-to-reach places, eliminate the lack of knowledge in algorithms for processing data from seismic sensors of angular movements, classify and systematize sources, improve prediction accuracy, implement algorithms for locating and tracking sources. The aim of the work was to create algorithms for processing seismic data for classifying signal sources, determining the distance and azimuth to the point of excitation of surface waves.
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Ramola, Jyoti. "A Low-Cost, High-Performance Digital Signal Processor (DSP) for Audio Applications." Mathematical Statistician and Engineering Applications 71, no. 1 (January 1, 2022): 303–12. http://dx.doi.org/10.17762/msea.v71i1.2123.
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Digital audio signal processing has become increasingly common in multimedia systems as a result of the development of general-purpose digital signal processors (DSP processors) and high-precision oversampling analog-to-digital (A/D) converters. Nevertheless, the solution based on standard DSP chips could be too expensive and power-hungry for portable and home entertainment audio systems. As a result, it is necessary to locate an alternative solution that is both low-cost and low-power. In the context of digital audio applications, this paper will describe how a DSP (Digital Signal Processor) is created, as well as how its architecture functions. The proposed digital signal processor (DSP) has six stages of pipeline with a fixed 24-bit data format, and each stage has 125 instructions. The instructions for the audio signal processing are provided in a very specific manner. Each and every command is handled within the confines of a single cycle.
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Manuliak, I. Z., S. I. Melnychuk, Yu Yo Striletskyi, and V. M. Harasymiv. "Gas flow measuring system using signal processing on the basis of entropy estimations." Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, no. 5 (2020): 125–30. http://dx.doi.org/10.33271/nvngu/2021-5/125.
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Purpose. To increase the accuracy of gas flow measurement in tachometric transducers based on the improvement of structural, hardware and algorithmic support of information and measuring systems. Methodology. The gas consumption value is determined by the parameters of information and measurement signals. Sensor signals interacting with the environment are traditionally processed on the basis of amplitude and frequency methods. The research methodology is based on the information theory, methods of statistical and spectral analysis, digital signal processing, the theory of gas dynamics, based on mathematical modeling in a computational experiment, as well as the theory of errors and measurement results uncertainty. The statistical characteristics of the measuring signals of the converter presented in the unitary basis are studied. Findings. The conducted research resulted in development of an information-measuring system to control the sensitivity threshold of the transducers of the primary volume and the volume of gas consumption based on the developed primary transducer, which allows providing relative standard uncertainty of cost determination within 0.5%. A special processor has been developed to calculate the entropy estimates of signal information. Originality. For the first time, a method for the formation and processing of information-measuring signals, which is based on the use of pressure pulsations due to the movement of the measuring element of the converter in the toroidal measuring cell, is proposed. Implementation of the measuring element of a spherical converter, whose density is almost commensurable with the density of the controlled medium is offered. Practical value. The proposed method allows providing a lower sensitivity threshold compared to the industrial implementation of tachometric type transducers.
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Saponjic, Djordje, and Vojislav Arandjelovic. "Realization of a digital rate meter as an IIR digital filter by implementing an optimized signal processing algorithm." Nuclear Technology and Radiation Protection 24, no. 2 (2009): 126–31. http://dx.doi.org/10.2298/ntrp0902126s.
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By applying the well known dualism: mean count rate - mean time between successive pulses - the equivalence between an IIR digital filter and a preset count digital rate meter has been demonstrated. By using a bank of four second order IIR filters and an optimized automated algorithm for filter selection, a practical realization of a preset count rate meter giving good tradeoff between statistical fluctuations and speed of response, particularly at low count rates such as background monitoring, is presented. The presented solution is suitable for designing portable count rate meters. The designed prototype is capable of operating up to 3600 pulses per second with an accuracy of over 4% in steady-state and response times of 1 second for the rising edge and 2 seconds for the falling edge of the mean count rate step-change.
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Liu, Lei, Peng Sun, Yubo Lang, and Jingjiao Li. "CFA-Based Splicing Forgery Localization Method via Statistical Analysis." IET Signal Processing 2024 (April 16, 2024): 1–11. http://dx.doi.org/10.1049/2024/9929900.
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The color filter array of the camera is an effective fingerprint for digital forensics. Most previous color filter array (CFA)-based forgery localization methods perform under the assumption that the interpolation algorithm is linear. However, interpolation algorithms commonly used in digital cameras are nonlinear, and their coefficients vary with content to enhance edge information. To avoid the impact of this impractical assumption, a CFA-based forgery localization method independent of linear assumption is proposed. The probability of an interpolated pixel value falling within the range of its neighboring acquired pixel values is computed. This probability serves as a means of discerning the presence and absence of CFA artifacts, as well as distinguishing between various interpolation techniques. Subsequently, curvature is employed in the analysis to select suitable features for generating the tampering probability map. Experimental results on the Columbia and Korus datasets indicate that the proposed method outperforms the state-of-the-art methods and is also more robust to various attacks, such as noise addition, Gaussian filtering, and JPEG compression with a quality factor of 90.
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Osenin, Yu I., and V. P. Voitenko. "DEVICE FOR DIAGNOSING A RAIL TRACK WITH ADAPTATION TO CONDITIONS WITH NOT CONTROLLED ACOUSTIC NOISE." Science and Transport Progress, no. 11 (June 25, 2006): 60–62. http://dx.doi.org/10.15802/stp2006/18621.
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The paper suggests a railway track diagnostic device adaptable to the conditions of uncontrolled acoustic interferences of man-caused origin propagating in the rail material by means of using the spectral analysis based upon the Fourier transformation, digital filtration and statistical signal processing. The device block diagram and its operation are considered.
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Shatagin, Dmitrii, Andrei Galkin, Alexander N. Osmehin, and Natalia Klochkova. "Cyber-Physical Hybrid Processing System Digital Twin." Materials Science Forum 1037 (July 6, 2021): 119–24. http://dx.doi.org/10.4028/www.scientific.net/msf.1037.119.
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The article proposes a method for obtaining a digital twin of the process of 3D printing by electric arc surfacing using an ensemble of machine learning methods. On the basis of the structural-parametric approach, a set of diagnostic parameters for the signals of current strength, voltage and acoustic emission was determined. Using exploratory analysis, the significance of each diagnostic parameter was assessed. A complex of statistical models has been developed to assess the stability of 3D printing processes using decision trees. Their optimal parameters and efficiency have been determined.
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Zima, Daria, Darya Sokolova, and Alexander Spector. "Spatiotemporal processing of broadband signals based on the linear prediction model." Proceedings of the Russian higher school Academy of sciences, no. 4 (January 20, 2021): 17–31. http://dx.doi.org/10.17212/1727-2769-2020-4-17-31.
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The main developments in the field of radar surveillance systems are aimed at studying their functioning, taking into account the influence of various factors, such as the effect of interference. The most important thing seems to be the detection of a broadband signal, which makes it possible to increase the range and speed resolution. This raises the problem of suppressing broadband interference with existing methods. The paper develops methods for processing broadband signals in the presence of active interference as applied to the use in systems with various variants of spatio-temporal antenna elements, in particular on the example of linear antenna arrays. The approach is based on the representation of signals and interference recorded by a digital antenna array in the form of multidimensional spatiotemporal processes, i.e. functions of spatial and temporal coordinates. This is due to both the spatial distribution of the antenna array elements and the spatial distribution of interference. Bayesian signal detector is the optimal algorithm and has the best characteristics, but at the same time its practical implementation is extremely difficult, carried out in the field of spatiotemporal coordinates. The investigated processing algorithms are based on the linear prediction model, i.e. by using the model of a Markov random process to describe interference on spatially distributed antenna elements. Particular attention is paid to the development of algorithms that can be implemented with limited computing resources and work in real time, which is a problem of statistical methods of signal processing.
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Su, K., D. Kundur, and D. Hatzinakos. "Statistical invisibility for collusion-resistant digital video watermarking." IEEE Transactions on Multimedia 7, no. 1 (February 2005): 43–51. http://dx.doi.org/10.1109/tmm.2004.840617.
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Aguayo-Tapia, Sarahi, Gerardo Avalos-Almazan, Jose de Jesus Rangel-Magdaleno, and Mario R. A. Paternina. "Broken Bar Fault Detection Using Taylor–Fourier Filters and Statistical Analysis." Entropy 25, no. 1 (December 27, 2022): 44. http://dx.doi.org/10.3390/e25010044.
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Broken rotor bars in induction motors make up one of the typical fault types that are challenging to detect. This type of damage can provoke adverse effects on the motors, such as mechanical and electrical stresses, together with an increase in electricity consumption, causing higher operative costs and losses related to the maintenance times or even the motor replacement if the damage has led to a complete failure. To prevent such situations, diverse signal processing algorithms have been applied to incipient fault detection, using different variables to analyze, such as vibrations, current, or flux. To counteract the broken rotor bar damage, this paper focuses on a motor current signal analysis for early broken bar detection and classification by using the digital Taylor–Fourier transform (DTFT), whose implementation allows fine filtering and amplitude estimation with the final purpose of achieving an incipient fault detection. The detection is based on an analysis of variance followed by a Tukey test of the estimated amplitude. The proposed methodology is implemented in Matlab using the O-splines of the DTFT to reduce the computational load compared with other methods. The analysis is focused on groups of 50-test of current signals corresponding to different damage levels for a motor operating at 50% and 75% of its full load.
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Blamey, Peter J. "Adaptive Dynamic Range Optimization (ADRO): A Digital Amplification Strategy for Hearing Aids and Cochlear Implants." Trends in Amplification 9, no. 2 (March 2005): 77–98. http://dx.doi.org/10.1177/108471380500900203.
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Adaptive dynamic range optimization (ADRO) is an amplification strategy that uses digital signal processing techniques to improve the audibility, comfort, and intelligibility of sounds for people who use cochlear implants and/or hearing aids. The strategy uses statistical analysis to select the most information-rich section of the input dynamic range in multiple-frequency channels. Fuzzy logic rules control the gain in each frequency channel so that the selected section of the dynamic range is presented at an audible and comfortable level. The ADRO processing thus adaptively optimizes the dynamic range of the signal in multiple-frequency channels. Clinical studies show that ADRO can be fitted easily to all degrees of hearing loss for hearing aids and cochlear implants in a direct and intuitive manner, taking the preferences of the listener into account. The result is high acceptance by new and experienced hearing aid users and strong preferences for ADRO compared with alternative amplification strategies. The ADRO processing is particularly well suited to bimodal and hybrid stimulation which combine electric and acoustic stimulation in opposite ears or in the same ear, respectively.
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Rabia Aslam Khan, Muhammad Bilal Butt, and Sabreena Nawaz. "Genomic Signal Processing Methods in DNA Mapping Schemes for Prediction of Exon in a Gene Using Digital Filters." International Journal for Electronic Crime Investigation 7, no. 3 (September 20, 2023): 61–68. http://dx.doi.org/10.54692/ijeci.2023.0703162.
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Genomic signal processing (GSP) is an engineering domain involved with the analysis of genomic data using digital signal processing (DSP) approaches after transformation of the sequence of genome to numerical sequence. One challenge of GSP is how to minimize the error of detection of the protein coding region in a specified deoxyribonucleic acid (DNA) sequence with a minimum processing time. Since the type of numerical representation of a DNA sequence extremely affects the prediction accuracy and precision. The impact of different DNA statistical representations on the identification of coding sequences (exons) was researched. In this study using the IIR inverse Chepyshev filter for twenty benchmark human genes. In order to accomplish this, the sensitivity, specificity, and correlation coefficient of the four most modern DNA numerical representation schemes GCC, FNO, atomic number, and 2-bit binary were measured and contrasted with those of EIIP, the most used technique for locating protein-coding regions.
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Isakov, O. V., and S. S. Voitusik. "Comparative analysis of digital noise generated by additive Fibonacci generators." Ukrainian Journal of Information Technology 5, no. 1 (2023): 67–76. http://dx.doi.org/10.23939/ujit2023.01.067.
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Noise generators and pseudorandom number generators (PRNGs) are widely used in the field of information technology, including cybersecurity, for modeling, authorization key generation, and technical protection of information. It has been found that the characteristics of digital noise directly depend on the chosen PRNG algorithm. To determine the quality of the generated noise, special tests are performed, which are primarily applied to the sequence generated by the PRNG. The results of digital noise generated by an PRNG based on four different algorithms of additive Fibonacci generators (AFG) are investigated. The choice of generators of the same type allowed us to analyze the effect of different modifications on the final result of the generated sequences to determine their advantages and disadvantages. Digital signal processing techniques such as frequency, autocorrelation and visual analysis, signal-to-noise ratio, and statistical tests of the NIST package were used to test the noise and generated sequences. Functions for interpreting the obtained data were developed using the MATLAB (DSP System Toolbox) application package and the C programming language for automating NIST tests. It has been found that for effective testing, specific stages and their sequence should be determined: determination of the PRNG period, statistical tests of the NIST package, calculation of the autocorrelation function, and other methods of digital signal processing. It was found that modification of one AFG by using a carry bit (MAFG2) does not improve the results of the generated sequence, unlike the PIKE algorithm, which consists of three AFGs. The MAFG algorithm showed better results during the period testing and at the same time passed NIST tests, unlike the unmodified version. The dependence between the order of the generated sequences and the results of their autocorrelation function was revealed. It is proposed that, in addition to general statistical tests, applied tests should be carried out when choosing or developing a new generator, its effectiveness should be checked under the conditions required by existing standards and requirements. The compliance of the generated digital noise with the requirements for devices for technical protection of information, namely the protection of speech information, has been established.
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BORGNAT, PIERRE, PATRICE ABRY, PATRICK FLANDRIN, CÉLINE ROBARDET, JEAN-BAPTISTE ROUQUIER, and ERIC FLEURY. "SHARED BICYCLES IN A CITY: A SIGNAL PROCESSING AND DATA ANALYSIS PERSPECTIVE." Advances in Complex Systems 14, no. 03 (June 2011): 415–38. http://dx.doi.org/10.1142/s0219525911002950.
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Community shared bicycle systems, such as the Vélo'v program launched in Lyon in May 2005, are public transportation programs that can be studied as a complex system composed of interconnected stations that exchange bicycles. They generate digital footprints that reveal the activity in the city over time and space, making possible a quantitative analysis of movements using bicycles in the city. A careful study relying on nonstationary statistical modeling and data mining allows us to first model the time evolution of the dynamics of movements with Vélo'v, that is mostly cyclostationary over the week with nonstationary evolutions over larger time-scales, and second to disentangle the spatial patterns to understand and visualize the flows of Vélo'v bicycles in the city. This study gives insights on the social behaviors of the users of this intermodal transportation system, the objective being to help in designing and planning policy in urban transportation.
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Ksendzuk, A. V., and K. O. Kozlov. "ADAPTIVE CORRELATOR IN NON-EMITTING RADAR SYSTEMS." Issues of radio electronics, no. 3 (March 20, 2019): 41–45. http://dx.doi.org/10.21778/2218-5453-2019-3-41-45.
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The paper discusses a new method of processing information in non‑emitting radar systems, whose work is based on the use of a signal from third‑party sources – television and radio broadcasting transmitters, as well as cellular base stations. An adaptive correlator for such radar stations is proposed. The method is based on the analysis of the autocorrelation function (ACF) of a transmitter signal and the adaptive formation of detection areas, based on the properties of the current ACF. Statistical quality parameters were introduced to evaluate the developed method and these parameters were estimated for the DVB‑T2 (Digital Video Broadcasting – Terrestrial) signal, in particular, the achievable characteristics by the side lobes of the lag time uncertainty function for such a signal are shown. It is noted that several adaptive correlators should be simultaneously implemented in non‑radiant radar. The results of processing real data confirm the effectiveness of the proposed method.
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Yudhistira Hidayat, Agung, Achmad Widodo, and Gunawan Dwi Haryadi. "Fault Diagnostic System Bearing Centrifugal Pump Using K-Means Method For Thermography Image And Signal Analysis Vibrations." MATEC Web of Conferences 159 (2018): 02006. http://dx.doi.org/10.1051/matecconf/201815902006.
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Numerous studies reported that infrared thermography and vibration are condition monitoring technology that is important and effective for doing a condition diagnostic of bearing centrifugal pump health without destructing or disturbing machine operational. This paper focuses on thermography image processing based on K-Mean color segmentation which will produce normal and abnormal condition features. Health diagnostic of bearing by processing of digital image, image clustering, segmentation and extraction. Extraction of image pattern is done by calculating the area of heat point and color feature bearing condition of RGB colour space and active contour segmentation in order to process and differentiate between normal and abnormal bearing image by statistical technique. The parameters that can be used as reference to classifying conditions are standard deviation, Mean, Variance, Skewness, Kurtosis, Vibration (RMS) and Shape features (area). Final step is determining the boundary condition between normal and abnormal using statistical logic method.
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Kim, Kyung Ki, and Yong-Bin Kim. "Statistical timing and leakage power analysis of PD-SOI digital circuits." Analog Integrated Circuits and Signal Processing 60, no. 1-2 (October 3, 2008): 127–36. http://dx.doi.org/10.1007/s10470-008-9220-7.
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KUMAR, RAJEEV. "A STATISTICAL APPROACH TO ROBUST VIDEO TEMPORAL INDEXING AND SEGMENTATION." International Journal of Wavelets, Multiresolution and Information Processing 05, no. 05 (September 2007): 769–83. http://dx.doi.org/10.1142/s021969130700204x.
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For video indexing, the problem of video cut detection remains largely an open problem because of the wide nature of transitions that occur in a digital video. This paper describes a shot boundary detection technique, which is an amalgamation of few statistical methods and measures, and robustly detects camera breaks in a full-motion video clip. The proposed algorithm incorporates a weighted histogram, an error-propagation technique for increased robustness, and a curve-fitting technique to extract partitions from the similarity curve for avoiding heuristically chosen threshold value. The algorithm has been validated on many video clips and is shown to give improved results, including for videos with rapid scanning, changes in illumination, fade-ins and fade-outs, and with special effects like dissolve and filters.
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Beskrovnii, Yaroslav, and Oleksii Larin. "Investigation of error in evaluation of spectral statistical characteristics of numerical solution of stochastic dynamic system." Bulletin of the National Technical University «KhPI» Series: Dynamics and Strength of Machines, no. 1 (December 31, 2021): 60–65. http://dx.doi.org/10.20998/2078-9130.2021.1.232387.
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In this paper, an algorithm for numerical simulations is developed for calculating a discrete dynamic system with a stochastic perturbation and an analysis of the quality of numerical solutions is carried out. For this, an algorithm for the numerical solution of a second-order differential equation with a stochastic right-hand side was developed and this algorithm was implemented as a program. The next step was to carry out a set of computational studies by varying the parameters of numerical integration with the subsequent assessment of their impact on the error and accuracy of simulations. To estimate the spectral density, the Welch periodogram method was used. To check the quality of simulations and assess the accuracy of solutions, it is proposed to compare the results of numerical integration and subsequent digital processing with analytical solutions that are known for the linear problem, given by the equation. As a result of the work, a comparative analysis of the dispersion of displacements relative to the lengths of signals from a different number of blocks was carried out, into which the signal is divided for the Welch method; the confidence interval of the error at different signal lengths and the confidence interval of the error with a different number of blocks at a certain signal length. Comparison of the variance with a different number of blocks showed that with a signal length of 30 s and from 90 s, there is a slight scatter of the variance values within an error of ± 5%.
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Owoeye, Oluwatobi M., and Olusola Abayomi Ojo-Omoniyi. "Deep Learning and Computer Vision: Machine Learning Analysis and Image Processing of Puromycin Treated Microscopy." International Journal of Current Microbiology and Applied Sciences 11, no. 6 (June 10, 2022): 119–33. http://dx.doi.org/10.20546/ijcmas.2022.1106.014.
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Digital image processing involves the usage of a functional algorithm to process images with special regions of interest. In most case scenarios, this is termed as an active aspect of digital signal processing; image processing comes with several rewards over analog image processing. Its relevance and application spans Autonomous Vehicles, Biometric fingerprint technologies as well as Face recognition applications. Reliable statistics through feature engineering from the image can be extracted and in turn serve as focus points of deep learning insights. Besides, its application in monitoring Climatic changes, Agricultural crop yields, security measures, industrial manufacturing as well as medical fields exponentially advances each day. Meanwhile, deep learning being a feature of Artificial Intelligence has brought forward several useful models that is being used as transfer base for further model accuracies and baselines. In this study, we make use of a certain Microscopy datasets, sampling one of the images for digital processing, in order to gain useful insights through Cropped Quantizing, Laplace Edge Detection and Gaussian noise with sigma methods respectively. The statistical results of the extracted image features through Support Vector Method (SVM) give accuracy of up to 75%.
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Kulikov, G. V., X. Kh Dang, and A. G. Kulikov. "Effect of synchronization system errors on the reception noise immunity of amplitude-phase shift keyed signals." Russian Technological Journal 11, no. 3 (June 3, 2023): 30–37. http://dx.doi.org/10.32362/2500-316x-2023-11-3-30-37.
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Objectives. An urgent task in the context of modern radio and television systems is to improve the quality and quantity of transmitted information. For example, the use of multiple amplitude-phase shift keyed (APSK) signals—16-APSK and 32-APSK—in digital satellite television systems of the Digital Video Broadcasting-Satellite2 (DVB-S2) standard made it possible to transmit 30% more data in the same frequency bands in comparison with the previous DVB-S standard. Such increases in information transmission rates impose more stringent requirements on hardware. An important role in the reception of APSK signals, as well as the signals of other coherent signal processing systems, is played by the stability of synchronization systems. The presence of operational errors can significantly reduce the quality of information reception. The aim of the present work was to analyze the effect of phase and clock synchronization errors on the reception noise immunity of APSK signals with a ring signal constellation structure.Methods. The study used statistical radio engineering methods informed by optimal signal reception theory.Results. The effect of phase and clock synchronization errors on the reception noise immunity of APSK signals having a signal constellation ring structure is analyzed. The dependencies of the bit error probability on the magnitude of the phase shift and the clock offset were characterized. The effect of synchronization errors on reception quality were compared with the known results for quadrature amplitude modulation (QAM) signals.Conclusions. At an acceptable energy loss of no more than 1 dB, the critical phase error can be considered as 2°-3°, while the critical clock error is 3-4%. A coherent receiver of APSK signals is more sensitive to the phase error of reference oscillations than a similar receiver of QAM signals, whereas clock errors have the same effect on the reception quality of these signals.
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Gall, Roman D., Maya E. Shevchenko, and Victor N. Malyshev. "Compensation of relay satellites heterodyne instability for locating terrestrial radio emission sources." Proceedings of the Russian higher school Academy of sciences, no. 3 (October 29, 2021): 17–31. http://dx.doi.org/10.17212/1727-2769-2021-3-17-31.
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Unintentional and intentional interference of terrestrial radio sources operating via geostationary relay satellites to legal users of satellite communication systems requires accurate determination of their location. Methods of terrestrial radio sources location are based on the calculation of an cross-аambiguity function by additive mixtures of signals and noise received from relay satellites. In the presence of frequency-phase instability of relay satellites heterodynes the retransmitted signals have phase distortions, which lead to a decrease in the signal-to-noise ratio (SNR) when calculating the cross- ambiguity function. The paper is aimed to study the effect of phase distortions caused by the instability of relay satellites heterodynes on SNR at the correlator output and to develop methods for their compensation based on statistical radio engineering and digital signal processing. The study of the proposed compensation methods was carried out by statistical simulation modeling. The SNR dependences at the correlator output on the duration of correlated signals for the model with a domi-nant frequency noise and frequency random walk have been obtained and a method for compensat-ing phase distortions caused by the instability of the relay satellites heterodynes has been developed. The energy gain has been estimated by applying the proposed compensation method. It has been shown that the developed method of compensation of relay satellites heterodynes instability allows achieving a significant gain in the SNR at the correlator output and contributes to increasing the probability of radio source signal detection from auxiliary relay satellites.
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Bessios, Anthony G., and Frank M. Caimi. "High-rate wireless data communications: An underwater acoustic communications framework at the physical layer." Mathematical Problems in Engineering 2, no. 6 (1996): 449–85. http://dx.doi.org/10.1155/s1024123x96000439.
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A variety of signal processing functions are performed by Underwater Acoustic Systems. These include: 1) detection to determine presence or absence of information signals in the presence of noise, or an attempt to describe which of a predetermined finite set of possible messages{mi,i,...,M}the signal represents; 2) estimation of some parameterθˆassociated with the received signal (i.e. range, depth, bearing angle, etc.); 3) classification and source identification; 4) dynamics tracking; 5) navigation (collision avoidance and terminal guidance); 6) countermeasures; and 7) communications. The focus of this paper is acoustic communications.There is a global current need to develop reliable wireless digital communications for the underwater environment, with sufficient performance and efficiency to substitute for costly wired systems. One possible goal is a wireless system implementation that insures underwater terminal mobility. There is also a vital need to improve the performance of the existing systems in terms of data-rate, noise immunity, operational range, and power consumption, since, in practice, portable high-speed, long range, compact, low-power systems are desired.We concede the difficulties associated with acoustic systems and concentrate on the development of robust data transmission methods anticipating the eventual need for real time or near real time video transmission. An overview of the various detection techniques and the general statistical digital communication problem is given based on a statistical decision theory framework. The theoretical formulation of the underwater acoustic data communications problem includes modeling of the stochastic channel to incorporate a variety of impairments and environmental uncertainties, and proposal of new compensation strategies for an efficient and robust receiver design.
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Singh, S. K., A. Muhammad, I. Umaru, M. M. Usman, M. N. Abdulkareem, M. I. Abubakar, and M. S. Nur. "COMPUTATIONAL ANALYSIS OF BUTTERWORTH AND CHEBYSHEV-I FILTERS USING BILINEAR TRANSFORMATION." International Journal of Research -GRANTHAALAYAH 10, no. 6 (June 30, 2022): 37–56. http://dx.doi.org/10.29121/granthaalayah.v10.i6.2022.4571.
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Due to the intense demands in advanced telecommunications during the last fifteen years for both higher spectrum band and better accuracy, the digital Infinite Impulse Response (IIR) filter has emerged as the basic component in both digital telecommunication and Digital Signal Processing (DSP) systems. In our research work reported in this paper we conducted meticulous investigation using computer simulation of the digital Infinite Impulse Response (IIR) filter to implement the Butterworth and Chebyshev I procedure with bilinear transformation algorithm aimed at both statistical analysis and computer simulation. Our simulation results reveal the comparative accuracy between digital filters and analog filters of the spectrum response in: i) absolute magnitude, ii) the magnitude in decibels (dB) and iii) phase. Conversely the filter selectivity and gain in decibel scale were numerically obtained.
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Shankar, Karthik V., Kailasnath K, and S. Babu Devasenapati. "Design of Fault Detection System for Automobile Power Train Using Digital Signal Processing and Soft Computing Techniques." International Journal of Manufacturing, Materials, and Mechanical Engineering 4, no. 3 (July 2014): 50–63. http://dx.doi.org/10.4018/ijmmme.2014070103.
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The increasing dependence of internal combustion engine in multitudes of application has mandated a detailed study on most of its subsystems. This paper focuses on predictive maintenance using machine learning based models. The transmission system of any power pace is often challenged due to sudden variation in applied load. Any fault in the transmission system could lead to the catastrophic failures hence need for this work. This paper deals with the identification of various fault conditions that happen in a transmission system using vibration signals acquired by an accelerometer. The acquired signals are processed to extract the statistical and spectral features. These features are used to build a machine learning model using decision tree or Random forest algorithm. The best combination of features and algorithm is evaluated and the results are presented.
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Chen, Qianhao, Wenqi Wu, and Wei Luo. "Lossless Compression of Sensor Signals Using an Untrained Multi-Channel Recurrent Neural Predictor." Applied Sciences 11, no. 21 (November 1, 2021): 10240. http://dx.doi.org/10.3390/app112110240.
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The use of sensor applications has been steadily increasing, leading to an urgent need for efficient data compression techniques to facilitate the storage, transmission, and processing of digital signals generated by sensors. Unlike other sequential data such as text sequences, sensor signals have more complex statistical characteristics. Specifically, in every signal point, each bit, which corresponds to a specific precision scale, follows its own conditional distribution depending on its history and even other bits. Therefore, applying existing general-purpose data compressors usually leads to a relatively low compression ratio, since these compressors do not fully exploit such internal features. What is worse, partitioning a bit stream into groups with a preset size will sometimes break the integrity of each signal point. In this paper, we present a lossless data compressor dedicated to compressing sensor signals which is built upon a novel recurrent neural architecture named multi-channel recurrent unit (MCRU). Each channel in the proposed MCRU models a specific precision range of each signal point without breaking data integrity. During compressing and decompressing, the mirrored network will be trained on observed data; thus, no pre-training is needed. The superiority of our approach over other compressors is demonstrated experimentally on various types of sensor signals.
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Błachnio, Józef, and Iwona Zabrocka. "IMAGE OF THE SURFACE OF GAS TURBINE BLADE AS A DIAGNOSTIC SIGNAL." Acta Mechanica et Automatica 7, no. 4 (December 1, 2013): 209–14. http://dx.doi.org/10.2478/ama-2013-0035.
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Abstract This paper outlines a non-destructive method that is suitable for evaluation of condition demonstrated by gas turbine blades and is based on digital processing of images acquired from the blade surface in visible light. To enable high clearness of these images the particular attention is paid to the problem of how to provide optimum conditions for investigations and mitigate geometrical distortions of images acquired from maintenance operations. The paper demonstrates that there are relationships between operation lifetime of blades and discoloration of their surfaces due to overheating of the blade material. These relationships are revealed by digital analysis of images acquired for the blade surfaces and expressed as statistical parameter of the first and second order. To improve unambiguity of the analysis results a low-pass filter was applied. It was demonstrated that these relationships are suitable for evaluation how much the status of the blade material microstructure is altered
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Kuharskaya, O. V., and E. Z. Savin. "Influence of Synchronization Signal Inaccuracy on DVB-T2 Local Content Insertion." Journal of the Russian Universities. Radioelectronics, no. 1 (April 17, 2018): 19–24. http://dx.doi.org/10.32603/1993-8985-2018-21-1-19-24.
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The article is aimed at specifying criteria of synchronization signal inaccuracy when DVB-T2 system local content re-placement cannot be carried out. Some settings of digital information stream are set as the initial data. The first part of the article specifies network delay calculation method. The second part of the article considers the signal cycle instability impact on estimation of local content device delay during its insertion in global information flow. Network delay saw-toothlike dependence on time is revealed, statistical parameters of synchronization signal instability are specified. The third part of the article deals with analysis of method of substitution of two independent information flows by regionali-zation device. A model of T2 superframes comprising baseband frames (BB frames) which belong to different physical layer pipes (PLP) is described. The conditions under which the local information insertion becomes impossible are de-fined. Besides, the article considers other reasons of failure during single frequency networks (SFN) processing of local content insertion dealing with synchronization error at different stages of information flow digital content generation and delivery to DVB-T2.
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Savchenko, V. V., and A. V. Savchenko. "Measurements method of the audio recordings acoustic quality indicator prepared for registration and processing in the Unified Biometric System." Izmeritel`naya Tekhnika, no. 12 (2019): 40–46. http://dx.doi.org/10.32446/0368-1025it.2019-12-40-46.
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We consider the task of automated quality control of sound recordings containing voice samples of individuals. It is shown that in this task the most acute is the small sample size. In order to overcome this problem, we propose the novel method of acoustic measurements based on relative stability of the pitch frequency within a voice sample of short duration. An example of its practical implementation using aninter-periodic accumulation of a speech signal is considered. An experimental study with specially developed software provides statistical estimates of the effectiveness of the proposed method in noisy environments. It is shown that this method rejects the audio recording as unsuitable for a voice biometric identification with a probability of 0,95 or more for a signal to noise ratio below 15 dB. The obtained results are intended for use in the development of new and modifying existing systems of collecting and automated quality control of biometric personal data. The article is intended for a wide range of specialists in the field of acoustic measurements and digital processing of speech signals, as well as for practitioners who organize the work of authorized organizations in preparing for registration samples of biometric personal data.
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Ermoshkin, V. I., S. B. Shatkovsky, A. V. Shcherbinko, and E. E. Fenyuk. "Method for measuring the azimuth of an aerial target for a meter-range radar." Issues of radio electronics, no. 3 (June 25, 2021): 26–31. http://dx.doi.org/10.21778/2218-5453-2021-3-26-31.
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The purpose of the study is to develop a new method that increases the accuracy of measuring the azimuth of an air target for stationary radars of the meter range of radio waves with a fixed antenna array and a small number of antenna elements. For this, the known methods are considered and their disadvantages are revealed. The new method proposed by the authors uses a digital radiation pattern with a fast Fourier transform after intra-pulse processing of signals from the receiving elements of the antenna array at a given frequency. To refine the azimuth, an inverse fast Fourier transform is used, followed by signal processing and repeated measurement for each target with a small step. Calculations and test results are presented. Comparisons of statistical estimates of the mean and standard deviation of azimuth measurement tests by various methods are presented. The scientific novelty and directions for further development of the topic with the use of the results obtained have been established.
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Liang, Yan, Gao Yan, and Chun Xia Qi. "A DCT-Domain System for Digital Watermarking." Applied Mechanics and Materials 321-324 (June 2013): 2609–12. http://dx.doi.org/10.4028/www.scientific.net/amm.321-324.2609.
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Digital watermarking has been proposed as a solution to the problem of copyright protection of multimedia data in a networked environment. It makes possible to tightly associated to a digital document a code allowing the identification of the data creator, owner, authorized consumer, and so on. In this paper a new DCT-domain system for digital watermarking algorithm for digital images is presented: the method, which operates in the frequency domain, embeds a pseudo-random sequence of scrambled image in a selected set of DCT coefficients. After embedding, the watermark is adapted to the image by exploiting the masking characteristics of the human visual system, thus ensuring the watermark invisibility. By exploiting the statistical properties of the embedded sequence, the mark can be reliably extracted without resorting to the original uncorrupted image. Experimental results demonstrate that the watermark is robust to several signal processing techniques, including JPEG compression, cut, fuzzy, addition of noise, and sharpen.
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MEZENTSEV, O. V., S. V. MIRONYUK, G. G. OSINOVYY, and K. V. KOZIS. "STRUCTURES OF ADAPTIVE SIGNAL PROCESSING SYSTEMS FOR RADAR SENSORS OF EXTERNAL INFORMATION FOR CORRELATION-EXTREME AIRCRAFT NAVIGATION SYSTEMS." Kosmìčna nauka ì tehnologìâ 29, no. 6 (December 9, 2023): 102–6. http://dx.doi.org/10.15407/knit2023.06.102.
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During the guidance of the aircraft on the final part of the flight, it is affected, along with other external factors, by interferences of various (artificial or natural) origins. These interferences have various effects on the receiving elements of the antenna array of the radar sensor of external information. Due to the variability and rapidity of the complex interference situation, adaptive interference protection systems are the most effective in combating these interferences. It is known that the use of adaptive processing systems allows for overcoming the practically inevitable a priori uncertainty of statistical characteristics of signals and interference of various origins. At present, due to the development of digital technology, new methods and devices for adaptive signal processing against the back- ground of interference have appeared. Thus, the arsenal of methods of adaptation to Gaussian disturbances has been supplemented by methods involving the inversion (direct or recurrent) of the most plausible estimates of correlation matrices of disturbances or their regularized varieties. Wide possibilities of adaptation are opened up in modern radar stations with multi-element phased antenna ar- rays, which provide for digital information processing. Due to the very high speed of the aircraft during the operation of its correlation- extreme guidance system, as well as due to the dynamic and non-stationary interference environment, an important requirement for adaptive anti-jamming systems is their speed. The effectiveness of adaptive processing of signals against the background of interference can be significantly increased by using reliable a priori information. The paper considers a method of increasing the speed of adaptive protection systems against radar interference of various origins by taking into account a priori information about the central symmetry of the receiving channels of radar sensors of external information of correlation-extreme aircraft navigation systems. It is shown that taking into account such a priori information as the central symmetry of the receiving channels of radar sensors of external informa- tion leads to a corresponding change in the structure of devices for adaptive signal processing in the conditions of interference in these sensors and as a consequence, to an increase in their speed.