Adaptive Filtering in the Wavelet Transform Domain Via Genetic Algorithms

Author(s):  
Frank Moore ◽  
Pat Marshall ◽  
Eric Balster
2011 ◽  
Vol 2-3 ◽  
pp. 176-181
Author(s):  
Yong Jun Shen ◽  
Guang Ming Zhang ◽  
Shao Pu Yang ◽  
Hai Jun Xing

Two de-noising methods, named as the averaging method in Gabor transform domain (AMGTD) and the adaptive filtering method in Gabor transform domain (AFMGTD), are presented in this paper. These two methods are established based on the correlativity of the source signals and the background noise in time domain and Gabor transform domain, that is to say, the uncorrelated source signals and background noise in time domain would still be uncorrelated in Gabor transform domain. The construction and computation scheme of these two methods are investigated. The de-noising performances are illustrated by some simulation signals, and the wavelet transform is used to compare with these two new de-noising methods. The results show that these two methods have better de-noising performance than the wavelet transform, and could reduce the background noise in the vibration signal more effectively.


2018 ◽  
Vol 12 (8) ◽  
pp. 1437-1445 ◽  
Author(s):  
Chuxi Yang ◽  
Yan Zhao ◽  
Shigang Wang

Author(s):  
D. S. Wickramanayake ◽  
H. E. Bez ◽  
E. A. Edirisinghe

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