Results 11 to 20 of about 26,456 (261)
A Hybrid Algorithm for Noise Suppression of MEMS Accelerometer Based on the Improved VMD and TFPF
Micromachines, 2022 High-G MEMS accelerometer (HGMA) is a new type of sensor; it has been widely used in high precision measurement and control fields. Inevitably, the accelerometer output signal contains random noise caused by the accelerometer itself, the hardware circuit
Yongjun Zhou, Huiliang Cao, Tao Guo
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Block-Adaptive Rényi Entropy-Based Denoising for Non-Stationary Signals
Sensors, 2022 This paper approaches the problem of signal denoising in time-variable noise conditions. Non-stationary noise results in variable degradation of the signal’s useful information content over time.
Nicoletta Saulig +3 more
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Signal Denoising Based on Duffing Oscillators System
IEEE Access, 2020 Signal denoising is an important aspect of signal processing. It is a meaningful direction to solve this problem by using chaotic oscillator. As a kind of chaotic oscillator, Duffing oscillator is often used in the field of periodic signal or pulse ...
Wenmao Luo, Yingliu Cui
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Radar Complex Intermediate Frequency Signal Denoising Based on Convolutional Auto-Encoder Network
IEEE Access, 2023 In radar systems, target state features are commonly extracted from intermediate frequency signals. However, these signals often have a low signal-to-noise ratio due to noisy environments and limitations of the radar hardware.
Haihua Xie, Yi Yuan, Sanyou Zeng
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Using AutoEncoders for Radio Signal Denoising [PDF]
Proceedings of the 15th ACM International Symposium on QoS and Security for Wireless and Mobile Networks, 2019 We investigated the use of a Deep Learning approach to radio signal de-noising. This data-driven approach has does not require explicit use of expert knowledge to set up the parameters of the denoising procedure and grants great flexibility across many channel conditions.
Almazrouei E. +4 more
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Sensors, 2019 In this paper, a novel hybrid method combining adaptive chirp mode pursuit (ACMP) with an adaptive multiscale Savitzky−Golay filter (AMSGF) based on adaptive moving average (AMA) is proposed for offline denoising micro-electromechanical system ...
Jingjing He, Changku Sun, Peng Wang
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Applied Sciences, 2020 Microseismic signal denoising is of great significance for P wave, S wave first arrival picking, source localization, and focal mechanism inversion. Therefore, an Empirical Mode Decomposition (EMD), Compressed Sensing (CS), and Soft-thresholding (ST ...
Xiang Li +4 more
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The Journal of Engineering, 2019 In this article, a machine learning method to classify signal with Gaussian noise based on denoising auto encoder (DAE) and convolutional neural network (CNN) is proposed. We combine denoising autoencoder's denoising ability with CNN's feature extraction
Jun Wang +3 more
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A time-frequency denoising method for single-channel event-related EEG
Frontiers in Neuroscience, 2022 IntroductionElectroencephalogram (EEG) acquisition is easily affected by various noises, including those from electrocardiogram (ECG), electrooculogram (EOG), and electromyogram (EMG).
Wenqiang Yan, Yongcheng Wu
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Fuzzy multiwavelet denoising on ECG signal [PDF]
Electronics Letters, 2003 Since different multiwavelets, pre- and post-filters have different impulse and frequency responses characteristics, different multiwavelets, pre- and post-filters should be selected, integrated and applied at different noise levels if a signal is corrupted by an additive white Gaussian noise (AWGN).
Ho, C Y-F +4 more
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