JOURNAL ARTICLE
The ε-normalized sign regressor least mean square (NSRLMS) adaptive algorithm
Abstract
In this paper, expressions are derived for the steady-state and tracking excess-mean-square error (EMSE) of the ε-normalized sign regressor least mean square (NSRLMS) adaptive algorithm. Finally, it is shown that simulations performed for both the cases of white and correlated Gaussian regressors substantiate very well the theory developed.
Keywords:
Sign (mathematics) Mean squared error Square (algebra) Algorithm Gaussian Least mean squares filter Steady state (chemistry) Mathematics Mean square Tracking (education) Computer science Adaptive filter Control theory (sociology) Statistics Artificial intelligence Mathematical analysis Physics Geometry
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Topics
Advanced Adaptive Filtering Techniques
Physical Sciences → Engineering → Computational Mechanics
Blind Source Separation Techniques
Physical Sciences → Computer Science → Signal Processing
Speech and Audio Processing
Physical Sciences → Computer Science → Signal Processing
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