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Statistical analysis of the LMS adaptive algorithm subjected to a symmetric dead-zone nonlinearity at the adaptive filter output by Márcio Holsbach Costa; Leandro Ronchini Ximenes; José Carlos Moreira Bermudez is a Computer Science article available to read on EtoBox.

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This work presents a statistical analysis of the Least Mean Square (LMS) adaptive algorithm subjected to the existence of a symmetric dead-zone nonlinearity at the adaptive filter output. Such configuration can be representative of low-cost active noise control systems where the canceling signal drives a class B power amplifier or a nonlinear actuator. Recursive deterministic equations are derived for the mean coefficient and mean-square error behaviors assuming Gaussian signals and slow adaptation. The steady-state algorithm behavior is determined for given filter parameters and degree of nonlinearity. Monte Carlo simulations and laboratory experiments are presented which corroborate the theoretical results.

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Author

Márcio Holsbach Costa; Leandro Ronchini Ximenes; José Carlos Moreira Bermudez

Publisher

Elsevier Science; Elsevier ; Elsevier BV (ISSN 0165-1684)

Published

2008

Language

EN

Field

Computer Science (Physical Sciences)