Paper Info
Title
Normalized recursive least adaptive threshold nonlinear errors algorithm
Abstract
This paper proposes a new adaptation algorithm named Normalized Recursive Least Adaptive Threshold Nonlinear Errors (NRLATNE) algorithm for complex-domain adaptive filters which makes the filters fast convergent for correlated filter inputs and robust against two types of impulse noise: one is found in additive observation noise and another at filter input. Analysis of the proposed NRLATNE algorithm is fully developed to theoretically calculate filter convergence behavior. Through experiments with some examples, we demonstrate the effectiveness of the proposed algorithm in improving the filter performance. Good agreement is observed between simulated and theoretically calculated filter convergence that shows the validity of the analysis.
Year
Venue
Keywords
2015
European Signal Processing Conference
Adaptive filter,recursive least squares,impulse noise,adaptive threshold,nonlinear error,normalization
Field
DocType
ISSN
Digital filter,Control theory,Computer science,Algorithm,Adaptive filter,Kernel adaptive filter,Recursive filter,Multidelay block frequency domain adaptive filter,Nonlinear filter,Recursive least squares filter,Filter design
Conference
2076-1465
Citations 
PageRank 
References 
0
0.34
4
Authors
1
Name
Order
Citations
PageRank
Shin'ichi Koike1174.93