A new method for low-rank transform domain adaptive filtering

2000 ◽  
Vol 48 (4) ◽  
pp. 1097-1109 ◽  
Author(s):  
B. Raghothaman ◽  
D.A. Linebarger ◽  
D. Begusic
Keyword(s):  
Adaptive Filtering ◽  
New Method ◽  
Low Rank ◽  
Transform Domain ◽  
Rank Transform

scholarly journals Two De-Noising Methods Based on Gabor Transform

2011 ◽  
Vol 2-3 ◽  
pp. 176-181
Author(s):  
Yong Jun Shen ◽  
Guang Ming Zhang ◽  
Shao Pu Yang ◽  
Hai Jun Xing
Keyword(s):  
Wavelet Transform ◽  
Adaptive Filtering ◽  
Time Domain ◽  
Background Noise ◽  
Averaging Method ◽  
Vibration Signal ◽  
Gabor Transform ◽  
Transform Domain ◽  
Computation Scheme ◽  
Source Signals

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.

Transform domain conjugate gradient algorithm for adaptive filtering

2000 ◽  
Vol 17 (1) ◽  
pp. 69-76
Author(s):  
Yuexian Zou ◽  
S. C. Chan ◽  
T. S. Ng ◽  
Xianchi Xiao
Keyword(s):  
Adaptive Filtering ◽  
Conjugate Gradient ◽  
Conjugate Gradient Algorithm ◽  
Gradient Algorithm ◽  
Transform Domain
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