Results 1 to 10 of about 590,374 (288)
EM-DeepSD: A Deep Neural Network Model Based on Cell-Free DNA End-Motif Signal Decomposition for Cancer Diagnosis [PDF]
DiagnosticsBackground and Objectives: The accurate discrimination between patients with and without cancer using their cell-free DNA (cfDNA) is crucial for early cancer diagnosis.
Zhi-Yang Zhao +6 more
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Error reduction in EMG signal decomposition.
J Neurophysiol, 2014 Decomposition of the electromyographic (EMG) signal into constituent action potentials and the identification of individual firing instances of each motor unit in the presence of ambient noise are inherently probabilistic processes, whether performed manually or with automated algorithms. Consequently, they are subject to errors.
Kline JC, De Luca CJ.
europepmc +4 more sources
Multivariate Nonlinear Sparse Mode Decomposition and Its Application in Gear Fault Diagnosis
IEEE Access, 2021 Multi-channel signal has more abundant and accurate state characteristic information than single channel signal. How to separate fault characteristic information from the multi-channel signal is the key of fault diagnosis.
Haiyang Pan +3 more
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Remote Sensing, 2022 Atmospheric lidar is susceptible to the influence of light attenuation, sky background light, and detector dark currents during the detection process. This results in a large amount of noise in the lidar return signal.
Zhiyuan Li +5 more
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Adaptive Complex Variational Mode Decomposition for Micro-Motion Signal Processing Applications
Sensors, 2021 In order to suppress the strong clutter component and separate the effective fretting component from narrow-band radar echo, a method based on complex variational mode decomposition (CVMD) is proposed in this paper.
Saiqiang Xia +5 more
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Photovoltaic Power Quality Analysis Based on the Modulation Broadband Mode Decomposition Algorithm
Energies, 2021 The Broadband Mode Decomposition (BMD) method was previously proposed to solve the Gibbs phenomenon that occurs during photovoltaic signal decomposition; its main idea is to build a dictionary which contains signal features, and to search in the ...
Zucheng Wang +7 more
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Temporal Graph Signal Decomposition [PDF]
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, 2021 Temporal graph signals are multivariate time series with individual components associated with nodes of a fixed graph structure. Data of this kind arises in many domains including activity of social network users, sensor network readings over time, and time course gene expression within the interaction network of a model organism.
McNeil, Maxwell +2 more
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Energies, 2021 Accurately predicting surface vibration signals of diesel engines is the key to evaluating the operation quality of diesel engines. Based on an improved empirical mode decomposition and extreme learning machine algorithm, the characteristics of diesel ...
Yan Shen +3 more
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Contrast of multi‐resolution analysis approach to transhumeral phantom motion decoding
CAAI Transactions on Intelligence Technology, 2021 In signal processing, multiresolution decomposition techniques allow for the separation of an acquired signal into sub levels, where the optimal level within the signal minimises redundancy, uncertainties, and contains the information required for the ...
Ejay Nsugbe +3 more
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Research on a Noise Reduction Method Based on Multi-Resolution Singular Value Decomposition
Applied Sciences, 2020 Reducing noise pollution in signals is of great significance in the field of signal detection. In order to reduce the noise in the signal and improve the signal-to-noise ratio (SNR), this paper takes the singular value decomposition theory as the ...
Gang Zhang +6 more
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