Adaptive filters based on the high order error statistics

This paper presents convergence analyses of the stochastic gradient adaptive algorithms based on high order error power criteria. In particular, our attention has focused on investigating the statistical behaviour of the least mean absolute third (LMAT) and the least mean fourth (LMF) adaptive algor...

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Veröffentlicht in:1996 IEEE Asia Pacific Conference on Circuits and Systems Proceedings S. 109 - 112
Hauptverfasser: Sung Ho Cho, Sang Duck Kim
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 1996
Schlagworte:
Adaptive algorithm
Adaptive filters
Algorithm design and analysis
Convergence
Error analysis
Finite impulse response filter
Least squares approximation
Nonlinear equations
Signal processing algorithms
Stochastic processes
ISBN:9780780337022, 0780337026
Online-Zugang:Volltext
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Zusammenfassung:This paper presents convergence analyses of the stochastic gradient adaptive algorithms based on high order error power criteria. In particular, our attention has focused on investigating the statistical behaviour of the least mean absolute third (LMAT) and the least mean fourth (LMF) adaptive algorithms. For each algorithm, under a set of mild assumptions, we have derived nonlinear evolution equations that characterize the mean and mean-squared behaviour of the algorithm. Computer simulation examples show fairly good agreement between the theoretical and actual behaviour of the two algorithms.
ISBN:9780780337022
0780337026
DOI:10.1109/APCAS.1996.569231