Singular Value Decomposition Based Feature Extraction Technique for Physiological Signal Analysis

2010 ◽  
Vol 36 (3) ◽  
pp. 1769-1777 ◽  
Author(s):  
Cheng-Ding Chang ◽  
Chien-Chih Wang ◽  
Bernard C. Jiang
Keyword(s):  
Feature Extraction ◽  
Singular Value Decomposition ◽  
Signal Analysis ◽  
Singular Value ◽  
Extraction Technique ◽  
Physiological Signal ◽  
Value Decomposition ◽  
Feature Extraction Technique

Improving TF-IDF with Singular Value Decomposition (SVD) for Feature Extraction on Twitter

2017 ◽  
Author(s):  
Ammar Ismael Kadhim ◽  
Yu-N Cheah ◽  
Inaam Abbas Hieder ◽  
Rawaa Ahmed Ali
Keyword(s):  
Feature Extraction ◽  
Singular Value Decomposition ◽  
Singular Value ◽  
Value Decomposition

scholarly journals Subspace-based signal analysis using singular value decomposition

1993 ◽  
Vol 81 (9) ◽  
pp. 1277-1308 ◽  
Author(s):  
A.-J. Van Der Veen ◽  
E.F. Deprettere ◽  
A.L. Swindlehurst
Keyword(s):  
Singular Value Decomposition ◽  
Signal Analysis ◽  
Singular Value ◽  
Value Decomposition

Research on Fault Feature Extraction Method of the Wind Turbine Gearbox Based on SVD and Improved HHT

2012 ◽  
Vol 220-223 ◽  
pp. 785-788
Author(s):  
Chang Zheng Chen ◽  
Quan Gu ◽  
Bo Zhou
Keyword(s):  
Feature Extraction ◽  
Singular Value Decomposition ◽  
Wind Turbine ◽  
Extraction Method ◽  
Random Noise ◽  
Singular Value ◽  
Wind Turbine Gearbox ◽  
Feature Extraction Method ◽  
Value Decomposition ◽  
Fault Feature Extraction

This paper researches fault feature extraction method based on singular value decomposition and the improved HHT method for non-stationary characteristics of wind turbine gearbox vibration signal. Firstly, through the signal phase space reconstruction, the singular value decomposition as a pre-filter, to preprocessing the signal, effectively weaken the random noise. Then using EEMD to improve the HHT method, decompose the denoising signal into a series of different time scales component of intrinsic mode functions. The fault characteristics of the signal are extracted by the Hilbert transform. Finally, simulating gearbox fault experiment to verify the effectively of the proposed method.

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