Convergence of the DLMS algorithm with decreasing step size

Sang Sik Ahn; Peter J. Voltz

Convergence of the DLMS algorithm with decreasing step size

Electrical and Computer Engineering

Research output: Contribution to journal › Conference article › peer-review

Abstract

Convergence analyses for the least mean square algorithm with update delay (DLMS) exist, but most of them are based on the unrealistic independence assumption between successive input vectors. In this paper we consider the DLMS algorithm with decreasing step size μ(n) = a/n, a > 0 and prove the almost-sure convergence of the algorithm under the mixing input, satisfaction of the law of large numbers, and uniformly bounded input assumptions.

Original language	English (US)
Pages (from-to)	1854-1857
Number of pages	4
Journal	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	3
State	Published - 1996
Event	Proceedings of the 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP. Part 1 (of 6) - Atlanta, GA, USA Duration: May 7 1996 → May 10 1996

ASJC Scopus subject areas

Software
Signal Processing
Electrical and Electronic Engineering

Cite this

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title = "Convergence of the DLMS algorithm with decreasing step size",

abstract = "Convergence analyses for the least mean square algorithm with update delay (DLMS) exist, but most of them are based on the unrealistic independence assumption between successive input vectors. In this paper we consider the DLMS algorithm with decreasing step size μ(n) = a/n, a > 0 and prove the almost-sure convergence of the algorithm under the mixing input, satisfaction of the law of large numbers, and uniformly bounded input assumptions.",

author = "Ahn, {Sang Sik} and Voltz, {Peter J.}",

year = "1996",

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journal = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",

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

note = "Proceedings of the 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP. Part 1 (of 6) ; Conference date: 07-05-1996 Through 10-05-1996",

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AU - Ahn, Sang Sik

AU - Voltz, Peter J.

PY - 1996

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N2 - Convergence analyses for the least mean square algorithm with update delay (DLMS) exist, but most of them are based on the unrealistic independence assumption between successive input vectors. In this paper we consider the DLMS algorithm with decreasing step size μ(n) = a/n, a > 0 and prove the almost-sure convergence of the algorithm under the mixing input, satisfaction of the law of large numbers, and uniformly bounded input assumptions.

AB - Convergence analyses for the least mean square algorithm with update delay (DLMS) exist, but most of them are based on the unrealistic independence assumption between successive input vectors. In this paper we consider the DLMS algorithm with decreasing step size μ(n) = a/n, a > 0 and prove the almost-sure convergence of the algorithm under the mixing input, satisfaction of the law of large numbers, and uniformly bounded input assumptions.

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M3 - Conference article

AN - SCOPUS:0029725481

SN - 0736-7791

VL - 3

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EP - 1857

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

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

T2 - Proceedings of the 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP. Part 1 (of 6)

Y2 - 7 May 1996 through 10 May 1996

ER -

Convergence of the DLMS algorithm with decreasing step size

Abstract

ASJC Scopus subject areas

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