scholarly journals Convergence Evaluation of a Random Step-Size NLMS Adaptive Algorithm in System Identification and Channel Equalization

10.5772/16262 ◽  
2011 ◽  
Author(s):  
Shihab Jimaa
Keyword(s):  
System Identification ◽  
Adaptive Algorithm ◽  
Channel Equalization ◽  
Step Size ◽  
Random Step

scholarly journals Discrete wavelet transform-based RI adaptive algorithm for system identification

2020 ◽  
Vol 10 (3) ◽  
pp. 2383
Author(s):  
Mohammad Shukri Salman ◽  
Alaa Eleyan ◽  
Bahaa Al-Sheikh
Keyword(s):  
Wavelet Transform ◽  
System Identification ◽  
Convergence Rate ◽  
Discrete Wavelet Transform ◽  
Adaptive Algorithm ◽  
Convergence Rates ◽  
Recursive Least Squares ◽  
Discrete Wavelet ◽  
Step Size ◽  
Autocorrelation Matrix

In this paper, we propose a new adaptive filtering algorithm for system identification. The algorithm is based on the recursive inverse (RI) adaptive algorithm which suffers from low convergence rates in some applications; i.e., the eigenvalue spread of the autocorrelation matrix is relatively high. The proposed algorithm applies discrete-wavelet transform (DWT) to the input signal which, in turn, helps to overcome the low convergence rate of the RI algorithm with relatively small step-size(s). Different scenarios has been investigated in different noise environments in system identification setting. Experiments demonstrate the advantages of the proposed DWT recursive inverse (DWT-RI) filter in terms of convergence rate and mean-square-error (MSE) compared to the RI, discrete cosine transform LMS (DCTLMS), discrete-wavelet transform LMS (DWT-LMS) and recursive-least-squares (RLS) algorithms under same conditions.

A Variable Step Size LMS Adaptive Filtering Algorithm and Simulations Based on Computational Verb Theory

2013 ◽  
Vol 756-759 ◽  
pp. 3972-3976 ◽  
Author(s):  
Li Hui Sun ◽  
Bao Yu Zheng
Keyword(s):  
Adaptive Filtering ◽  
Adaptive Algorithm ◽  
Linear Functional ◽  
Functional Relationship ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Step Size ◽  
Filtering Algorithm ◽  
Variable Step ◽  
Simulation Results

Based on traditional LMS algorithm, variable step LMS algorithm and the analysis for improved algorithm, a new variable step adaptive algorithm based on computational verb theory is put forward. A kind of sectorial linear functional relationship is established between step parameters and the error. The simulation results show that the algorithm has the advantage of slow change which is closely to zero. And overcome the defects of some variable step size LMS algorithm in adaptive steady state value is too large.

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