A true stochastic gradient adaptive algorithm for applications using nonlinear actuators

This work considers the practical situation where adaptive systems are subject to a saturation nonlinearity at the output of the adaptive filter. Such is the case in active control of noise and vibration. A new adaptive algorithm is proposed which implements the true stochastic gradient approach to...

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Bibliographic Details
Published in:2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221) Vol. 6; pp. 3489 - 3492 vol.6
Main Authors: Costa, M.H., Bermudez, J.C.M.
Format: Conference Proceeding
Language:English
Published: IEEE 2001
Subjects:
Active noise reduction
Adaptive algorithm
Adaptive filters
Adaptive systems
Hardware
Mean square error methods
Steady-state
Stochastic processes
Stochastic resonance
Vibration control
ISBN:0780370414, 9780780370418
ISSN:1520-6149
Online Access:Get full text
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Summary:This work considers the practical situation where adaptive systems are subject to a saturation nonlinearity at the output of the adaptive filter. Such is the case in active control of noise and vibration. A new adaptive algorithm is proposed which implements the true stochastic gradient approach to the nonlinear problem. Deterministic nonlinear recursions are derived which model the mean weight and mean square error behaviors. The steady-state behavior is also studied. The practical aspects of nonlinearity estimation and hardware implementation are addressed. It is shown that the new algorithm outperforms the LMS algorithm even for considerable errors in estimating the nonlinearity parameters.
ISBN:0780370414
9780780370418
ISSN:1520-6149
DOI:10.1109/ICASSP.2001.940593