Transient analysis of adaptive filters with error nonlinearities

Tareq Y. Al-Naffouri; Ali H. Sayed

doi:10.1109/TSP.2002.808108

Transient analysis of adaptive filters with error nonlinearities

Tareq Y. Al-Naffouri^*, Ali H. Sayed

^*Corresponding author for this work

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

124 Scopus citations

Abstract

This paper develops a unified approach to the transient analysis of adaptive filters with error nonlinearities. In addition to deriving earlier results in a unified manner, the approach also leads to new performance results without restricting the regression data to being Gaussian or white. The framework is based on energy-conservation arguments and avoids the need for explicit recursions for the covariance matrix of the weight-error vector.

Original language	English (US)
Pages (from-to)	653-663
Number of pages	11
Journal	IEEE Transactions on Signal Processing
Volume	51
Issue number	3
DOIs	https://doi.org/10.1109/TSP.2002.808108
State	Published - Mar 2003
Externally published	Yes

Keywords

Adaptive filter
Energy-conservation
Error nonlinearity
Feedback analysis
Mean-square-error error
Steady-state analysis
Transient analysis

ASJC Scopus subject areas

Signal Processing
Electrical and Electronic Engineering

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/TSP.2002.808108

Cite this

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title = "Transient analysis of adaptive filters with error nonlinearities",

abstract = "This paper develops a unified approach to the transient analysis of adaptive filters with error nonlinearities. In addition to deriving earlier results in a unified manner, the approach also leads to new performance results without restricting the regression data to being Gaussian or white. The framework is based on energy-conservation arguments and avoids the need for explicit recursions for the covariance matrix of the weight-error vector.",

keywords = "Adaptive filter, Energy-conservation, Error nonlinearity, Feedback analysis, Mean-square-error error, Steady-state analysis, Transient analysis",

author = "Al-Naffouri, {Tareq Y.} and Sayed, {Ali H.}",

note = "Funding Information: Manuscript received March 12, 2001; revised October 23, 2002. This work was supported in part by the National Science Foundation under Grants CCR-9732376, ECS-9820765, and CCR-0208573. The work of T. Y. Al-Naffouri was also supported in part by a fellowship from King Fahd University of Petroleum and Minerals, Dharan, Saudi Arabia. The associate editor coordinating the review of this paper and approving it for publication was Dr. Dennis R. Morgan.",

year = "2003",

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doi = "10.1109/TSP.2002.808108",

language = "English (US)",

volume = "51",

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journal = "IEEE Transactions on Signal Processing",

issn = "1053-587X",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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T1 - Transient analysis of adaptive filters with error nonlinearities

AU - Al-Naffouri, Tareq Y.

AU - Sayed, Ali H.

N1 - Funding Information: Manuscript received March 12, 2001; revised October 23, 2002. This work was supported in part by the National Science Foundation under Grants CCR-9732376, ECS-9820765, and CCR-0208573. The work of T. Y. Al-Naffouri was also supported in part by a fellowship from King Fahd University of Petroleum and Minerals, Dharan, Saudi Arabia. The associate editor coordinating the review of this paper and approving it for publication was Dr. Dennis R. Morgan.

PY - 2003/3

Y1 - 2003/3

N2 - This paper develops a unified approach to the transient analysis of adaptive filters with error nonlinearities. In addition to deriving earlier results in a unified manner, the approach also leads to new performance results without restricting the regression data to being Gaussian or white. The framework is based on energy-conservation arguments and avoids the need for explicit recursions for the covariance matrix of the weight-error vector.

AB - This paper develops a unified approach to the transient analysis of adaptive filters with error nonlinearities. In addition to deriving earlier results in a unified manner, the approach also leads to new performance results without restricting the regression data to being Gaussian or white. The framework is based on energy-conservation arguments and avoids the need for explicit recursions for the covariance matrix of the weight-error vector.

KW - Adaptive filter

KW - Energy-conservation

KW - Error nonlinearity

KW - Feedback analysis

KW - Mean-square-error error

KW - Steady-state analysis

KW - Transient analysis

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DO - 10.1109/TSP.2002.808108

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JO - IEEE Transactions on Signal Processing

JF - IEEE Transactions on Signal Processing

IS - 3

ER -

Transient analysis of adaptive filters with error nonlinearities

Abstract

Keywords

ASJC Scopus subject areas

UN SDGs

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