scholarly journals Performance Analysis and Enhancement of Spline Adaptive Filtering based on Adaptive Step-size Variable Leaky Least Mean Square Algorithm

2020 ◽  
Vol 5 (6) ◽  
pp. 642-651
Author(s):  
Sethakarn Prongnuch ◽  
Suchada Sitjongsataporn
Keyword(s):  
Performance Analysis ◽  
Adaptive Filtering ◽  
Mean Square ◽  
Least Mean Square ◽  
Step Size ◽  
Adaptive Step Size ◽  
Least Mean Square Algorithm ◽  
Adaptive Step ◽  
Size Variable

Implementation of Single and Multiple Adaptive Step-Size Algorithm to ANC

2007 ◽  
Vol 130 (1) ◽  
Author(s):  
Yesim Sabah ◽  
Masaaki Okuma ◽  
Minoru Okubo
Keyword(s):  
Steady State ◽  
Noise Control ◽  
Active Noise Control ◽  
Mean Square ◽  
Least Mean Square ◽  
Step Size ◽  
Adaptive Step Size ◽  
Active Noise ◽  
Adaptive Step ◽  
State Error

The purpose of this paper is to investigate a modified adaptive step-size algorithm and implement an active noise control (ANC) system. It is well known that there is a tradeoff between steady state error and convergence rate depending on the step size. This study shows that the new algorithm can track changes in the dynamic characteristics of the ANC system as well as produce a low steady state error. Simulation results are presented to compare the performance of the new algorithm to the basic least mean square (LMS) algorithm. Although there have been several studies of adaptive step-size algorithms, no quantitative analysis has yet been reported for real time active noise control application as far as the authors know. Experimental results are presented for a duct system. The results indicate that the new algorithm provides better performance than the fixed step-size filtered-X least mean square (FXLMS) algorithm.

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