New insights in the analysis of polynomial adaptive filters

Charles W. Therrien; W. Kenneth Jenkins

New insights in the analysis of polynomial adaptive filters

Charles W. Therrien
, W. Kenneth Jenkins

Research output: Contribution to conference › Paper › peer-review

Abstract

New results are reported on the structure of the correlation matrix for the data vector in Volterra second order adaptive filters for a general colored Gaussian input process. The structure becomes apparent when the input to the quadratic part of the filter is represented as a Kronecker product of the vector of terms to the linear part, and the redundant terms in the product are not removed. This approach leads to bounds on the eigenvalues of the correlation matrix which characterize the performance of LMS algorithms, and suggestions for possibly improved nonlinear adaptive filtering algorithms.

Original language	English (US)
Pages	382-385
Number of pages	4
State	Published - 1996
Event	Proceedings of the 1996 7th IEEE Digital Signal Processing Workshop - Loen, Norway Duration: Sep 1 1996 → Sep 4 1996

Other

Other	Proceedings of the 1996 7th IEEE Digital Signal Processing Workshop
City	Loen, Norway
Period	9/1/96 → 9/4/96

All Science Journal Classification (ASJC) codes

Signal Processing
Electrical and Electronic Engineering

Cite this

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title = "New insights in the analysis of polynomial adaptive filters",

abstract = "New results are reported on the structure of the correlation matrix for the data vector in Volterra second order adaptive filters for a general colored Gaussian input process. The structure becomes apparent when the input to the quadratic part of the filter is represented as a Kronecker product of the vector of terms to the linear part, and the redundant terms in the product are not removed. This approach leads to bounds on the eigenvalues of the correlation matrix which characterize the performance of LMS algorithms, and suggestions for possibly improved nonlinear adaptive filtering algorithms.",

author = "Therrien, \{Charles W.\} and Jenkins, \{W. Kenneth\}",

year = "1996",

language = "English (US)",

pages = "382--385",

note = "Proceedings of the 1996 7th IEEE Digital Signal Processing Workshop ; Conference date: 01-09-1996 Through 04-09-1996",

}

TY - CONF

T1 - New insights in the analysis of polynomial adaptive filters

AU - Therrien, Charles W.

AU - Jenkins, W. Kenneth

PY - 1996

Y1 - 1996

N2 - New results are reported on the structure of the correlation matrix for the data vector in Volterra second order adaptive filters for a general colored Gaussian input process. The structure becomes apparent when the input to the quadratic part of the filter is represented as a Kronecker product of the vector of terms to the linear part, and the redundant terms in the product are not removed. This approach leads to bounds on the eigenvalues of the correlation matrix which characterize the performance of LMS algorithms, and suggestions for possibly improved nonlinear adaptive filtering algorithms.

AB - New results are reported on the structure of the correlation matrix for the data vector in Volterra second order adaptive filters for a general colored Gaussian input process. The structure becomes apparent when the input to the quadratic part of the filter is represented as a Kronecker product of the vector of terms to the linear part, and the redundant terms in the product are not removed. This approach leads to bounds on the eigenvalues of the correlation matrix which characterize the performance of LMS algorithms, and suggestions for possibly improved nonlinear adaptive filtering algorithms.

UR - https://www.scopus.com/pages/publications/0029766768

UR - https://www.scopus.com/pages/publications/0029766768#tab=citedBy

M3 - Paper

AN - SCOPUS:0029766768

SP - 382

EP - 385

T2 - Proceedings of the 1996 7th IEEE Digital Signal Processing Workshop

Y2 - 1 September 1996 through 4 September 1996

ER -

New insights in the analysis of polynomial adaptive filters

Abstract

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All Science Journal Classification (ASJC) codes

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