Results 1 to 10 of about 26,456 (261)

Chaotic signal denoising based on energy selection TQWT and adaptive SVD [PDF]

Scientific Reports, 2023
Aiming at the problem of denoising chaotic signals with low signal-to-noise ratio and unknown dynamic system parameters, a new chaotic signal denoising algorithm is proposed, which combines adjustable Q-factor wavelet transform (TQWT) and adaptive ...
Xinlu Yang, Wenbo Wang
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EEMD and Multiscale PCA-Based Signal Denoising Method and Its Application to Seismic P-Phase Arrival Picking [PDF]

Sensors, 2021
Signal denoising is one of the most important issues in signal processing, and various techniques have been proposed to address this issue. A combined method involving wavelet decomposition and multiscale principal component analysis (MSPCA) has been ...
Kang Peng, Hongyang Guo, Xueyi Shang
doaj   +2 more sources

Denoising stacked autoencoders for transient electromagnetic signal denoising [PDF]

Nonlinear Processes in Geophysics, 2019
The transient electromagnetic method (TEM) is extremely important in geophysics. However, the secondary field signal (SFS) in the TEM received by coil is easily disturbed by random noise, sensor noise and man-made noise, which results in the difficulty ...
F. Lin, F. Lin, K. Chen, K. Chen, X. Wang, X. Wang, H. Cao, H. Cao, D. Chen, F. Chen   +9 more
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Optimal Wavelet Selection for Signal Denoising. [PDF]

IEEE Access
Wavelet denoising plays a key role in removing noise from signals and is widely used in many applications. In denoising, selection of the mother wavelet is desirable for maximizing the separation of noise and signal coefficients in the wavelet domain for effective noise thresholding. At present, wavelet selection is carried out in a heuristic manner or
Sahoo GR, Freed JH, Srivastava M.
europepmc   +4 more sources

Multi-Modal Joint Pulsed Eddy Current Sensor Signal Denoising Method Integrating Inductive Disturbance Mechanism [PDF]

Sensors
Pulsed eddy current (PEC) testing technology has been widely used in the field of non-destructive testing of metal grounding structures due to its wide-band excitation and response characteristics.
Yun Zuo, Gebiao Hu, Fan Gan, Zhiwu Zeng, Zhichi Lin, Xinxun Wang, Ruiqing Xu, Liang Wen, Shubing Hu, Haihong Le, Runze Wu, Jingang Wang   +11 more
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A reliable evaluation approach for multichannel signal denoising algorithms based on a novel arterial pulse acquisition system [PDF]

Heliyon
Background: Tactile sensors are utilized to measure multichannel pulse signals in pulse wave analysis (PWA). Owing to noise interferences, researchers have applied various denoising algorithms on multichannel pulse signals.
Chao Chen, Zhendong Chen, Yuqi Zhou, Yinan Hao, Bo Peng, Xiaohua Xie, Haiqing Xie   +6 more
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Fusion denoising algorithm for vibration signal of mine hoist with low signal-to-noise ratio

Gong-kuang zidonghua, 2023
Aiming at the nonlinear and low signal-to-noise ratio characteristics of mine hoist vibration signal in complex environments, a mine hoist vibration signal fusion denoising algorithm based on complete EEMD with adaptive noise (CEEMDAN) and adaptive ...
WANG Houchao, NIU Qiang, CHEN Pengpeng, XIA Shixiong   +3 more
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A nonlinear total variation based denoising method for electrostatic signal of low signal-to-noise ratio

Advances in Mechanical Engineering, 2022
Aero-engine electrostatic monitoring technology (EMT) is a novel and effective condition monitoring technology. With the help of EMT, effective monitoring of early failures can be achieved. Since the electrostatic monitoring of the running engine will be
Zhirong Zhong, Hongfu Zuo, Heng Jiang
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Bayesian multifractal signal denoising [PDF]

2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)., 2004
This work presents an approach for signal/image denoising in a semi-parametric frame. Our model is a wavelet-based one, which essentially assumes a minimal local regularity. This assumption translates into constraints on the multifractal spectrum of the signals.
Lévy Véhel, Jacques, Legrand, Pierrick
openaire   +2 more sources

Sparse Reconstruction for Enhancement of the Empirical Mode Decomposition-Based Signal Denoising

IEEE Access, 2020
Effective signal denoising methods are essential for science and engineering. In general, denoising algorithms may be either linear or non-linear. Most of the linear ones are unable to remove the noise from the real-world measurements.
Krzysztof Brzostowski
doaj   +1 more source