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Journal articles on the topic 'Signal approximation'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

Cheng, Bing, and Xiaokun Zhu. "A Multiresolution Approximation Theory of Fractal Transform." Fractals 05, supp01 (1997): 173–86. http://dx.doi.org/10.1142/s0218348x97000747.

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In this paper, we show that the fractal transform (FT) constitutes a multiresolution approximation to the square-integrable space L2(Td) for d≥1, where T is the interval (-∞,∞). This provides a theoretical basis for the successful applications of the fractal transform algorithms in signal/image encoding. There are many similarities between fractal-based and wavelet-based approximations. However, they are undamentally different from each other in many aspects. Fractal-based multiresolution approximation to signals/images is by a way of self-increasing model complexity, and wavelet-based multire

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Hyvärinen, Aapo. "Optimal Approximation of Signal Priors." Neural Computation 20, no. 12 (2008): 3087–110. http://dx.doi.org/10.1162/neco.2008.10-06-384.

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In signal restoration by Bayesian inference, one typically uses a parametric model of the prior distribution of the signal. Here, we consider how the parameters of a prior model should be estimated from observations of uncorrupted signals. A lot of recent work has implicitly assumed that maximum likelihood estimation is the optimal estimation method. Our results imply that this is not the case. We first obtain an objective function that approximates the error occurred in signal restoration due to an imperfect prior model. Next, we show that in an important special case (small gaussian noise),

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Piltan, Farzin, and Jong-Myon Kim. "Bearing Anomaly Recognition Using an Intelligent Digital Twin Integrated with Machine Learning." Applied Sciences 11, no. 10 (2021): 4602. http://dx.doi.org/10.3390/app11104602.

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In this study, the application of an intelligent digital twin integrated with machine learning for bearing anomaly detection and crack size identification will be observed. The intelligent digital twin has two main sections: signal approximation and intelligent signal estimation. The mathematical vibration bearing signal approximation is integrated with machine learning-based signal approximation to approximate the bearing vibration signal in normal conditions. After that, the combination of the Kalman filter, high-order variable structure technique, and adaptive neural-fuzzy technique is inte

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4

Mayorov, Boris. "Properties of Harmonic and Composite Half-Waves, Determination of the Uniform Time Sampling Interval of Digital Signal Processors." Informatics and Automation 21, no. 1 (2021): 95–125. http://dx.doi.org/10.15622/ia.2022.21.4.

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When building autonomous real-time systems (RTS), it is necessary to solve the problem of optimal multitasking loading of a number of parallel functioning digital signal processors. One of the reserves for achieving the desired result is the implementation of samples from the sensor signals of information about the magnitude of the signal most rarely in time. In this case, it is necessary to provide a linear or stepwise approximation of the signal by samples with an acceptable reconstruction error. One of the system tasks of these processors is filtering signals or limiting the spectrum to the

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SHANG, ZHAOWEI, YUAN YAN TANG, BIN FANG, JING WEN, and YAT ZHOU ONG. "MULTIRESOLUTION SIGNAL DECOMPOSITION AND APPROXIMATION BASED ON SUPPORT VECTOR MACHINES." International Journal of Wavelets, Multiresolution and Information Processing 06, no. 04 (2008): 593–607. http://dx.doi.org/10.1142/s0219691308002513.

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The fusion of wavelet technique and support vector machines (SVMs) has become an intensive study in recent years. Considering that the wavelet technique is the theoretical foundation of multiresolution analysis (MRA), it is valuable for us to investigate the problem of whether a good performance could be obtained if we combine the MRA with SVMs for signal approximation. Based on the fact that the feature space of SVM and the scale subspace in MRA can be viewed as the same Reproducing Kernel Hilbert Spaces (RKHS), a new algorithm named multiresolution signal decomposition and approximation base

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Srinivasan, Parthasarathy. "A Prony Method Variant which Surpasses the Adaptive LMS Filter in the Precision of the Output Signal’s Representation of the Input." Signal & Image Processing : An International Journal 15, no. 4 (2024): 01–09. http://dx.doi.org/10.5121/sipij.2024.15401.

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The Prony method for approximating signals comprising sinusoidal/exponential components is known through the pioneering work of Prony in his seminal dissertation in the year 1795. However, the Prony method saw the light of real world application only upon the advent of the computational era, which made feasible the extensive numerical intricacies and labor which the method demands inherently. The Adaptive LMS Filter which has been the most pervasive method for signal filtration and approximation since its inception in 1965 does not provide a consistently assured level of highly precise results

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Belyavsky, Grigory I., Nikita A. Mishin, and Konstantin E. Azhogin. "Signal Approximation Algorithm for Human Electroencephalograms Classification." UNIVERSITY NEWS. NORTH-CAUCASIAN REGION. NATURAL SCIENCES SERIES, no. 2 (222) (June 27, 2024): 12–20. http://dx.doi.org/10.18522/1026-2237-2024-2-12-20.

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The article examines the problem of classification of electroencephalograms (EEG), where noise in the signals, caused by various factors, prevents effective analysis and interpretation of the data. The main goal of the study is to analyze the effectiveness of a signal approximation algorithm using a wavelet technique with the next piece-wise approximation in order to effectively remove noise and subsequently solve the problem of signal classification using a convolutional neural network. The classification accuracy of the proposed algorithm with a low-pass filter is compared at different cutof

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Stoyanov, Stiliyan. "APPROXIMATION METHOD FOR DISCOVERY OF ANOMALOUS SIGNALS IN OPTICAL-ELECTRONIC DEVICES." Journal Scientific and Applied Research 17, no. 1 (2019): 9–12. http://dx.doi.org/10.46687/jsar.v17i1.266.

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The research is about registration of signals by optic-electronic devices. The subject of the current work is research of the approximative methods capability to discover anomalous signals in an impulse photometric device. The impulse photometric device ensures a high dimensional and timely resolution of the intensity distribution by natural optic emissions in the earth atmosphere and also light interference near the orbital station. The high spectral sensitivity and the dimensional resolution enable the research of fast processes, including pulsating polar lights, polar arcs, etc. When we dis

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9

Ray, Shashwati, and Vandana Chouhan. "Electrocardiogram reconstruction based on Hermite interpolating polynomial with Chebyshev nodes." Indonesian Journal of Electrical Engineering and Computer Science 36, no. 2 (2024): 837. http://dx.doi.org/10.11591/ijeecs.v36.i2.pp837-845.

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Electrocardiogram (ECG) signals generate massive volume of digital data, so they need to be suitably compressed for efficient transmission and storage. Polynomial approximations and polynomial interpolation have been used for ECG data compression where the data signal is described by polynomial coefficients only. Here, we propose approximation using hermite polynomial interpolation with chebyshev nodes for compressing ECG signals that consequently denoises them too. Recommended algorithm is applied on various ECG signals taken from MIT-BIH arrhythmia database without any additional noise as th

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10

Shashwati, Ray Vandana Chouhan. "Electrocardiogram reconstruction based on Hermite interpolating polynomial with Chebyshev nodes." Indonesian Journal of Electrical Engineering and Computer Science 36, no. 2 (2024): 837–45. https://doi.org/10.11591/ijeecs.v36.i2.pp837-845.

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Electrocardiogram (ECG) signals generate massive volume of digital data, so they need to be suitably compressed for efficient transmission and storage. Polynomial approximations and polynomial interpolation have been used for ECG data compression where the data signal is described by polynomial coefficients only. Here, we propose approximation using hermite polynomial interpolation with chebyshev nodes for compressing ECG signals that consequently denoises them too. Recommended algorithm is applied on various ECG signals taken from MIT-BIH arrhythmia database without any additional noise as th

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11

Hong. "Approximation of a Warship Passive Sonar Signal Using Taylor Expansion." Journal Of The Acoustical Society Of Korea 33, no. 4 (2014): 232. http://dx.doi.org/10.7776/ask.2014.33.4.232.

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12

DEDIEU, HERVÉ, and MACIEJ OGORZAŁEK. "CHAOS-BASED SIGNAL PROCESSING." International Journal of Bifurcation and Chaos 10, no. 04 (2000): 737–48. http://dx.doi.org/10.1142/s0218127400000517.

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Given a time series measured (or generated) by a known or an unknown dynamical system we address a series of problems which can be considered as advanced signal processing tasks, namely: (1) section-wise approximation of the measured signal by pieces of trajectories from a chosen nonlinear dynamical system (model); (2) signal restoration when the measured signal has been corrupted e.g. by quantization; (3) signal coding and compression. These tasks can be addressed using a new approach to the shadowing problem based on nonlinear observability problem. Its goal is to reproduce initial condition

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13

Howard, Roy M. "Arbitrarily Accurate Analytical Approximations for the Error Function." Mathematical and Computational Applications 27, no. 1 (2022): 14. http://dx.doi.org/10.3390/mca27010014.

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A spline-based integral approximation is utilized to define a sequence of approximations to the error function that converge at a significantly faster manner than the default Taylor series. The real case is considered and the approximations can be improved by utilizing the approximation erf(x)≈1 for |x|>xo and with xo optimally chosen. Two generalizations are possible; the first is based on demarcating the integration interval into m equally spaced subintervals. The second, is based on utilizing a larger fixed subinterval, with a known integral, and a smaller subinterval whose integral is t

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14

Zhao, Wenli, Linze Wang, and Jian Fan. "Theory and method for weak signal detection in engineering practice based on stochastic resonance." International Journal of Modern Physics B 31, no. 28 (2017): 1750212. http://dx.doi.org/10.1142/s0217979217502125.

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In this paper, the Kramers rate was derived using the Fokker–Planck (FP) equation with the condition of adiabatic approximation (the amplitude and frequency of signal detected are small [Formula: see text]) and the signal-to-noise ratio (SNR) was proved by means of Fourier transform and the power spectrum in bistable system. This is a concise and superior method to demonstrate the Kramers rate and SNR compared to the past methods. It is convenient for readers to understand. The SNR of the bistable system obtained shows that stochastic resonance (SR) can be used to realize energy transition fro

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15

Dziwoki, Grzegorz, and Marcin Kucharczyk. "On a Sparse Approximation of Compressible Signals." Circuits, Systems, and Signal Processing 39, no. 4 (2019): 2232–43. http://dx.doi.org/10.1007/s00034-019-01287-8.

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Abstract Many physical phenomena can be modeled by compressible signals, i.e., the signals with rapidly declining sample amplitudes. Although all the samples are usually nonzero, due to practical reasons such signals are attempted to be approximated as sparse ones. Because sparsity of compressible signals cannot be unambiguously determined, a decision about a particular sparse representation is often a result of comparison between a residual error energy of a reconstruction algorithm and some quality measure. The paper explores a relation between mean square error (MSE) of the recovered signal

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16

Uyematsu, Tomohiko, and Kohichi Sakaniwa. "A method for signal approximation using minimum norm signal." Electronics and Communications in Japan (Part I: Communications) 70, no. 3 (1987): 1–10. http://dx.doi.org/10.1002/ecja.4410700301.

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17

Ahadiat, Mohammad Reza, Paeiz Azmi, and Afrooz Haghbin. "The Mitigation of the Effect of Impulsive Noise in OFDM-PLC Systems." Journal of Research in Science, Engineering and Technology 3, no. 01 (2019): 18–25. http://dx.doi.org/10.24200/jrset.vol3iss01pp18-25.

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This paper proposes an new iterative method to recover the signals corrupted by impulsive noise in MIMO-OFDM systems over In-home PLC. In this iterative technique, preliminary decisions are made to get the impulsive noise detection algorithm for finding the locations and amplitudes of the impulses, and then signal estimation block for approximation the signals for two-branch 2*2 MIMO-OFDM at the receiver. In each iteration, this signals approximation are used to improve the noise estimate. After impulsive noise detection, an comparison - decision algorithm is employed to compare two noises est

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18

Choo, Youngmin, and Woojae Seong. "Modeling of Long-Range Reverberation Signal for Rough Bottom Consisting of Polygon Facets." Journal of Theoretical and Computational Acoustics 26, no. 04 (2018): 1850041. http://dx.doi.org/10.1142/s259172851850041x.

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To acquire a stable reverberation signal from an irregular ocean bottom, we derive the analytic surface integral of a scattered signal using Stokes’ theorem while approximating the bottom using a combination of polygon facets. In this approach, the delay difference in the elemental scattering area is considered, while the representative delay is used for the elemental scattering area in the standard reverberation model. Two different reverberation models are applied to a randomly generated rough bottom, which is composed of triangular facets. Their results are compared, and the scheme using an

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19

Bunting, Andrew, and Caroline Terquem. "Tidally induced stellar oscillations: converting modelled oscillations excited by hot Jupiters into observables." Monthly Notices of the Royal Astronomical Society 500, no. 2 (2020): 2711–31. http://dx.doi.org/10.1093/mnras/staa3394.

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ABSTRACT We calculate the conversion from non-adiabatic, non-radial oscillations tidally induced by a hot Jupiter on a star to observable spectroscopic and photometric signals. Models with both frozen convection and an approximation for a perturbation to the convective flux are discussed. Observables are calculated for some real planetary systems to give specific predictions. The photometric signal is predicted to be proportional to the inverse square of the orbital period, P−2, as in the equilibrium tide approximation. However, the radial velocity signal is predicted to be proportional to P−1

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20

MAKRAKIS, G. N., and E. K. SKARSOULIS. "ASYMPTOTIC APPROXIMATION OF OCEAN-ACOUSTIC PULSE PROPAGATION IN THE TIME DOMAIN." Journal of Computational Acoustics 12, no. 02 (2004): 197–215. http://dx.doi.org/10.1142/s0218396x04002225.

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Broadband and narrowband time-domain asymptotics are proposed for pulse propagation in range-independent ocean environments. The broadband approximation results by applying the stationary-phase method to the Fourier transform of the Green's function, expressed in terms of normal modes. The narrowband approximation is obtained by incorporating the shape function of the emitted signal — assumed Gaussian — into the phase term and applying the steepest-descent method. The roots of the frequency-derivative of the phase are located in the complex plane by using a second-order expansion of the eigenv

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21

Wu, Shaochong, Hongyuan Wang, Xunjiang Zheng, and Zhiqiang Yan. "Fluctuations in Refracted Star Signals Caused by the Stratospheric Internal Gravity Waves." Remote Sensing 16, no. 9 (2024): 1519. http://dx.doi.org/10.3390/rs16091519.

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The application of starlight refraction navigation to spacecraft and space weapons is a significant development. However, the irregular stratospheric atmosphere can cause fluctuations in relative light intensity and refraction angles of refracted stars, which need to be analyzed to provide guidance for system design and simulation verification. The internal gravity wave (IGW) is an important component of the irregular atmosphere. Based on the Rytov approximation, closed-form approximations were obtained, which can more intuitively reveal the relationship between the IGW parameters and the star

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22

Ky, Nguyen Xuan. "Signal analysis and weighted polynomial approximation." Studia Scientiarum Mathematicarum Hungarica 43, no. 2 (2006): 159–69. http://dx.doi.org/10.1556/sscmath.43.2006.2.2.

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We present applications of Hermite polynomials in signal analysis. Among other result, we give a characterization of the so-called time-frequency window functions in terms of the Hermite--Fourier coefficients, a Bernstein-type theorem for the best approximations of window functions by Hermite-functions, time-frequency approximations. Some analogues for Hankel-transforms will also be considered.

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23

Selesnick, Ivan, and Masoud Farshchian. "Sparse Signal Approximation via Nonseparable Regularization." IEEE Transactions on Signal Processing 65, no. 10 (2017): 2561–75. http://dx.doi.org/10.1109/tsp.2017.2669904.

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24

Combettes, P. L. "Signal recovery by best feasible approximation." IEEE Transactions on Image Processing 2, no. 2 (1993): 269–71. http://dx.doi.org/10.1109/83.217232.

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Boche, Holger, and Volker Pohl. "Signal representation and approximation–fundamental limits." European Transactions on Telecommunications 18, no. 5 (2007): 445–56. http://dx.doi.org/10.1002/ett.1194.

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Zhang, Xuebo, and Peixuan Yang. "An Improved Imaging Algorithm for Multi-Receiver SAS System with Wide-Bandwidth Signal." Remote Sensing 13, no. 24 (2021): 5008. http://dx.doi.org/10.3390/rs13245008.

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When the multi-receiver synthetic aperture sonar (SAS) works with a wide-bandwidth signal, the performance of the range-Doppler (R-D) algorithm is seriously affected by two approximation errors, i.e., point target reference spectrum (PTRS) error and residual quadratic coupling error. The former is generated by approximating the PTRS with the second-order term in terms of the instantaneous frequency. The latter is caused by neglecting the cross-track variance of secondary range compression (SRC). In order to improve the imaging performance in the case of wide-bandwidth signals, an improved R-D

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Kulkarni, Abhinav, Messaoud Ahmed Ouameur, and Daniel Massicotte. "Energy Efficient Wireless Signal Detection: A Revisit through the Lens of Approximate Computing." Electronics 13, no. 7 (2024): 1274. http://dx.doi.org/10.3390/electronics13071274.

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In the pursuit of energy efficiency in next-generation communication systems, approximate computing is emerging as a promising technique. In the proposed work, efforts are made to address the challenge of bridging the gap between the level of approximation and the Quality-of-Service (QoS) of the system. The application of approximate multiplication to wireless signal detection is explored systematically, illustrated by employing Truncated Multiplication (TM) on Quadrature Phase Shift Keying (QPSK) Minimum Mean Square Error (MMSE) detection. The irregularities induced by approximation in the mu

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Golikov, Ruslan Yu. "Piecewise linear approximation of a highly noisy signal waveform using least squares method." Journal Of Applied Informatics 17, no. 5 (2022): 116–24. http://dx.doi.org/10.37791/2687-0649-2022-17-5-116-124.

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The rising trend of computer technology using makes digital signal processing (DSP) techniques converted into numerical data sets particularly relevant. For the most part, they are quite complex and their use is not always justified for a wide range of applications. This determines the ongoing interest in heuristic algorithms that are based on simplified approaches and allow quickly obtaining approximation of estimates with the least work amount. This paper discusses a method of pulsed (single) aperiodic signal with a high level of noise component mathematical processing by approximating its s

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Putra, Darma Setiawan, and Yuril Umbu WW. "Feature Extraction of Facial Electromyograph (EMG) Signal for Aceh Languages Speech using Discrete Wavelet Transform (DWT)." Jurnal Inotera 4, no. 1 (2019): 31. http://dx.doi.org/10.31572/inotera.vol4.iss1.2019.id73.

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The facial electromyograph (FEMG) signal is a signal that occurs in the muscles of the contracted human face. This FEMG signal is one of the techniques used to study human speech recognition. It can be acquired by placing an electrode surface on the skin around the facial articulation muscle. Three types of muscles in this study are the masseter, risorius and depressor muscle. This study aims to extract and analyze the features in the FEMG signal. The extraction method is the discrete wavelet transform (DWT). The type of wavelet transform is Daubechies2 with level 5. After extraction and analy

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Jiang, Hongkai, Zheng Jia He, Chendong Duan, and Xue Feng Chen. "Gearbox Fault Diagnosis Using Adaptive Redundant Second Generation Wavelet." Key Engineering Materials 293-294 (September 2005): 95–102. http://dx.doi.org/10.4028/www.scientific.net/kem.293-294.95.

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Vibration signals acquired from a gearbox usually are complex, and it is difficult to detect the symptoms of an inherent fault in a gearbox. In this paper, an adaptive redundant second generation wavelet (ARSGW) based on second generation wavelet (SGW) is developed. It adopts data-based optimization algorithm to design the initial prediction operator and update operator at each scale. The initial operators are interpolated with zero, and then the redundant prediction operator and update operator are obtained. The splitting step in ARSGW is removed, the approximation signal at each scale is pre

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Hvozdzeu, Matsvei, and Maksim Karpovich. "DYNAMIC SIGNALS FILTRATION IN HIGH LEVEL NOISE CONDITION." Mokslas - Lietuvos ateitis 12 (May 13, 2020): 1–3. http://dx.doi.org/10.3846/mla.2020.11487.

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To examine the opportunity of measuring bulk solids consumption the experimental setup was developed. The main problem was the presence of a non-harmonic signal at the output. Almost always there are some difficulties to build measuring circuits using non-harmonic signals. It is necessary to use one of the approximation methods to receive a wanted signal without noise. For this purpose, the local approximation method was chosen. The developed technique confirmed its positive aspects and allowed to solve the questions that were posed before the experimental setup.

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Nahar, Ali. "Adaptive Symlet filter based on ECG baseline wander removal." Serbian Journal of Electrical Engineering 17, no. 2 (2020): 187–97. http://dx.doi.org/10.2298/sjee2002187n.

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In this paper, proposed a new approach of combining the hybrid soft computing technique called Adaptive Symlet Wavelet Transform (ASWT) filter. The baseline wanders (BW) noise removal from an ECG signals to minimize distortion of the S-T segment of the ECG signal specially that have high sampling frequencies. Therefore, when using Symlet Wavelet Transform (SWT) to analysis the ECG signal can cause problems to analysis, exclusively when examining the content of the ECG signal at low-frequency such as S-T segment. The corresponding frequency components of the approximation coefficients at level

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Sarkisov, S. V., S. Z. El-Salim, A. V. Bondarev, A. N. Korpusov, and P. A. Putilin. "Signal processing of nonlinear dynamic systems." Journal of Physics: Conference Series 2094, no. 2 (2021): 022057. http://dx.doi.org/10.1088/1742-6596/2094/2/022057.

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Abstract The paper considers Hermite polynomials that act as a self-similar basis for the decomposition of functions in phase space. It is shown that the equations of behavior of nonlinear dynamical systems are simplified. It is also noted that the wavelet decomposition over Hermite polynomials reduces the number of approximation coefficients and improves the quality of approximation.

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Butyrskiy, E. "Couscous-constant approximation in signal filtration task." National Security and Strategic Planning 2021, no. 1 (2021): 34–43. http://dx.doi.org/10.37468/2307-1400-2021-1-34-43.

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The paper considers the task of assessing the state of a nonlinear dynamic system, based on the couscous-linear approximation of non-linear functions included in the state and observa-tion equation. Examples of the method presented in filtration tasks are given and it is shown that the use of couscous-linear approximation allows at least half the margin of sampling error by the Kalman-Busey filter compared to the first-order approximation. Dynamic systems and processing algorithms in the form of vector-matrix equations have been obtained for multidi-mensional systems.

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Borkowski, Józef. "Minimization of Maximum Errors in Universal Approximation of the Unit Circle by a Polygon." Metrology and Measurement Systems 18, no. 3 (2011): 391–402. http://dx.doi.org/10.2478/v10178-011-0006-x.

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Minimization of Maximum Errors in Universal Approximation of the Unit Circle by a PolygonThis paper presents a universal approximation of the unit circle by a polygon that can be used in signal processing algorithms. Optimal choice of the values of three parameters of this approximation allows one to obtain a high accuracy of approximation. The approximation described in the paper has a universal character and can be used in many signal processing algorithms, such as DFT, that use the mathematical form of the unit circle. One of the applications of the described approximation is the DFT linear

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Baldychev, M., A. Bosyy, and O. Galtseva. "Model of forming a spatial-temporary radio frequency portrait of subscriber terminals in satellite communication systems monitoring." Bulletin of the Karaganda University. "Physics" Series 100, no. 4 (2020): 78–86. http://dx.doi.org/10.31489/2020ph4/78-86.

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Currently, the development of satellite communications systems (SCS) is associated with the development of signals of complex structure. The popularization and distribution of software-defined radio systems (Software-defined radio, SDR) are noted, which leads to a decrease of quality of functioning of the SCS. Promising areas of countering the unauthorized use of the time-frequency resource of the KA repeater are methods aimed at determining the location of subscriber terminals (ST) and analyzing the service and semantic parts of the transmitted message. Accounting for changes of physical para

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Mospan, Vladyslav, Denis Mospan, Olena Fomovskaya, Felix Fomovskii, and Alexey Yurko. "USE OF GAUSS FUNCTIONS FOR APPROXIMATION OF BIOLOGICAL SIGNALS." Transactions of Kremenchuk Mykhailo Ostrohradskyi National University, no. 3(128) (June 11, 2021): 111–16. http://dx.doi.org/10.30929/1995-0519.2021.3.111-116.

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Purpose. Currently, the method of mathematical analysis of various biological signals is increasingly used in medicine. Most of them are random and quasi-periodic processes, which greatly complicates the possibility of using an automated data processing process. Signals of this type include respiratory noises, phonocardiographic and electrocardiographic signals. The shape of the waves of the ECG signal is quite accurately described by asymmetric Gaussian pulses. It is possible to achieve the required approximation accuracy by introducing additional pulses to describe the diagnostically importa

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Серов, А. Н., А. А. Шатохин, Н. А. Серов, and П. К. Макарычев. "COMPARATIVE ANALYSIS OF RMS MEASUREMENT METHODS BASED ON SIGNAL SAMPLES APPROXIMATION." Южно-Сибирский научный вестник, no. 3(49) (June 30, 2023): 10–17. http://dx.doi.org/10.25699/sssb.2023.49.3.024.

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Среднее квадратическое значение (СКЗ) является одним из наиболее информативных параметров сигналов электрических сетей. Для измерения СКЗ в настоящее время применяются цифровые методы измерения, среди которых наиболее популярен метод, основанный на применении аппроксимирующего полинома нулевого порядка (или метод усреднения квадратов отсчетов). Вместе с тем, возможно применение и других методов измерения, основанных на аппроксимации полиномами более высоких порядков: первого и второго. В статье рассмотрены три цифровых метода измерения СКЗ, основанных на применении аппроксимирующих полиномов н

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Benammar, Mohieddine, Abdulrahman Alassi, Adel Gastli, Lazhar Ben-Brahim, and Farid Touati. "New Fast Arctangent Approximation Algorithm for Generic Real-Time Embedded Applications." Sensors 19, no. 23 (2019): 5148. http://dx.doi.org/10.3390/s19235148.

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Fast and accurate arctangent approximations are used in several contemporary applications, including embedded systems, signal processing, radar, and power systems. Three main approximation techniques are well-established in the literature, varying in their accuracy and resource utilization levels. Those are the iterative coordinate rotational digital computer (CORDIC), the lookup tables (LUTs)-based, and the rational formulae techniques. This paper presents a novel technique that combines the advantages of both rational formulae and LUT approximation methods. The new algorithm exploits the pse

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Karhunen, J. T., and J. Joutsensalo. "Sinusoidal frequency estimation by signal subspace approximation." IEEE Transactions on Signal Processing 40, no. 12 (1992): 2961–72. http://dx.doi.org/10.1109/78.175740.

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Zeng, Jin, Gene Cheung, and Antonio Ortega. "Bipartite Approximation for Graph Wavelet Signal Decomposition." IEEE Transactions on Signal Processing 65, no. 20 (2017): 5466–80. http://dx.doi.org/10.1109/tsp.2017.2733489.

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Lankhorst, Marc M., Marten D. Van Der Laan, and Wolfang A. Halang. "Wavelet-Based Signal Approximation with Genetic Algorithms." Systems Analysis Modelling Simulation 43, no. 11 (2003): 1503–28. http://dx.doi.org/10.1080/0232929022000002836.

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Wang, Rui, Xianjin Yang, Yazhen Yuan, Wei Chen, Kavita Bala, and Hujun Bao. "Automatic shader simplification using surface signal approximation." ACM Transactions on Graphics 33, no. 6 (2014): 1–11. http://dx.doi.org/10.1145/2661229.2661276.

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Shuman, David I., Pierre Vandergheynst, Daniel Kressner, and Pascal Frossard. "Distributed Signal Processing via Chebyshev Polynomial Approximation." IEEE Transactions on Signal and Information Processing over Networks 4, no. 4 (2018): 736–51. http://dx.doi.org/10.1109/tsipn.2018.2824239.

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Pan, Jian, Jun Tang, and Wei Zhu. "Sparse signal recovery via exponential metric approximation." Tsinghua Science and Technology 22, no. 01 (2017): 104–11. http://dx.doi.org/10.1109/tst.2017.7830900.

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Poliarus, Oleksandr, Yana Medvedovska, Yevhen Poliakov, Yevhenii Chepusenko, and Yurii Zharko. "SIMPLIFIED MODEL OF LINEAR INERTIAL MEASUREMENT SYSTEMS." Bulletin of Kharkov National Automobile and Highway University 1, no. 92 (2021): 119. http://dx.doi.org/10.30977/bul.2219-5548.2021.92.0.119.

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Problem. To increase the metrological reliability of measuring systems at technical objects, the number of sensors measuring the same process parameter is increased to several units and a model of a multi-channel measuring system is synthesized. This synthesis is usually based on the use of Markov's theory of linear filtering, but the presence of a connection between the input and output signals of the linear inertial system through the convolution integral significantly complicates the process of obtaining the optimal device. Goal. The aim of the article is to develop a method for approximati

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Thanh-Nghia, Nguyen, Nguyen Thanh-Hai, and Ngo Van-Thuyen. "Artifact elimination in ECG signal using wavelet transform." TELKOMNIKA Telecommunication, Computing, Electronics and Control 18, no. 2 (2020): 936–44. https://doi.org/10.12928/TELKOMNIKA.v18i2.14403.

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Electrocardiogram signal is the electrical actvity of the heart and doctors can diagnose heart disease based on this electrocardiogram signal. However, the electrocardiogram signals often have noise and artifact components. Therefore, one electrocardiogram signal without the noise and artifact plays an important role in heart disease diagnosis with more accurate results. This paper proposes a wavelet transform with three stages of decomposition, filter, and reconstruction for eliminating the noise and artifact in the electrocardiogram signal. The signal after decomposing produces approximation

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Chen, Yanlu, Lei Hu, Niaoqing Hu, and Jiyu Zeng. "A Synchrosqueezed Transform Method Based on Fast Kurtogram and Demodulation and Piecewise Aggregate Approximation for Bearing Fault Diagnosis." Sensors 24, no. 8 (2024): 2502. http://dx.doi.org/10.3390/s24082502.

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Synchrosqueezed transform (SST) is a time–frequency analysis method that can improve energy aggregation and reconstruct signals, which has been applied in the fields of medical treatment, fault diagnosis, and seismic wave processing. However, when dealing with time-varying signals, SST suffers from poor time–frequency resolution and is unable to deal with long signals. In order to accurately extract the characteristic frequency of variable speed rolling bearing faults, this paper proposes a synchrosqueezed transform method based on fast kurtogram and demodulation and piecewise aggregate approx

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Langhammer, Lukas, Roman Sotner, and Radek Theumer. "Various-Order Low-Pass Filter with the Electronic Change of Its Approximation." Sensors 23, no. 19 (2023): 8057. http://dx.doi.org/10.3390/s23198057.

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The design of a low-pass-frequency filter with the electronic change of the approximation characteristics of resulting responses is presented. The filter also offers the reconnection-less reconfiguration of the order (1st-, 2nd-, 3rd- and 4th-order functions are available). Furthermore, the filter offers the electronic control of the cut-off frequency of the output response. The feature of the electronic change in the approximation characteristics is investigated for the Butterworth, Bessel, Elliptic, Chebyshev and Inverse Chebyshev approximations. The design is verified by PSpice simulations

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Wang, Tong Yue, and Q. P. Sun. "Analysis of the Milling Acoustic Signal Using Wavelet Decomposition." Key Engineering Materials 693 (May 2016): 1503–8. http://dx.doi.org/10.4028/www.scientific.net/kem.693.1503.

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Vibration has a great influence on the cutting process and it can be detected by many signals. In this work, a set of experiments are conducted on Mikron UCP810 DURO high speed milling center with Fraisa carbide end mill for milling 2A12 aluminum workpiece, an acoustic method is used to detect the milling signals. The captured sound signals are analyzed using Matlab Daubechies5 wavelets with six levels of decomposition, the detail and approximation of the sound signal components are obtained. The analysis results demonstrate the relationship between the signal and the vibration.

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