Optimum error nonlinearities for long adaptive filters

Tareq Y. Al-Naffouri; Ali H. Sayed

doi:10.1109/ICASSP.2002.5744885

Optimum error nonlinearities for long adaptive filters

Tareq Y. Al-Naffouri, Ali H. Sayed

Research output: Contribution to journal › Article › peer-review

7 Scopus citations

Abstract

In this paper, we consider the class of adaptive filters with error nonlinearities. In particular, we derive an expression for the optimum nonlinearity that minimizes the steady-state error and attains the limit mandated by the Cramer-Rao bound of the underlying estimation process.

Original language	English (US)
Pages (from-to)	1373-1376
Number of pages	4
Journal	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	2
DOIs	https://doi.org/10.1109/ICASSP.2002.5744885
State	Published - 2002
Externally published	Yes

ASJC Scopus subject areas

Software
Signal Processing
Electrical and Electronic Engineering

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abstract = "In this paper, we consider the class of adaptive filters with error nonlinearities. In particular, we derive an expression for the optimum nonlinearity that minimizes the steady-state error and attains the limit mandated by the Cramer-Rao bound of the underlying estimation process.",

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doi = "10.1109/ICASSP.2002.5744885",

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AU - Sayed, Ali H.

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DO - 10.1109/ICASSP.2002.5744885

M3 - Article

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SN - 1520-6149

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JO - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

JF - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

ER -

Optimum error nonlinearities for long adaptive filters

Abstract

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