Mean-square analysis of normalized leaky adaptive filters

Ali H. Sayed; Tareq Y. Al-Naffouri

doi:10.1109/ICASSP.2001.940689

Mean-square analysis of normalized leaky adaptive filters

Ali H. Sayed, Tareq Y. Al-Naffouri

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

24 Scopus citations

Abstract

In this paper, we study leaky adaptive algorithms that employ a general scalar or matrix data nonlinearity. We perform mean-square analysis of this class of algorithms without imposing restrictions on the distribution of the input signal. In particular, we derive conditions on the step-size for stability, and provide closed form expressions for the steady-state performance.

Original language	English (US)
Pages (from-to)	3873-3876
Number of pages	4
Journal	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	6
DOIs	https://doi.org/10.1109/ICASSP.2001.940689
State	Published - 2001
Externally published	Yes

ASJC Scopus subject areas

Software
Signal Processing
Electrical and Electronic Engineering

Access to Document

10.1109/ICASSP.2001.940689

Cite this

@article{5c494d4e3683429b91214f7466aa9c92,

title = "Mean-square analysis of normalized leaky adaptive filters",

abstract = "In this paper, we study leaky adaptive algorithms that employ a general scalar or matrix data nonlinearity. We perform mean-square analysis of this class of algorithms without imposing restrictions on the distribution of the input signal. In particular, we derive conditions on the step-size for stability, and provide closed form expressions for the steady-state performance.",

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

year = "2001",

doi = "10.1109/ICASSP.2001.940689",

language = "English (US)",

volume = "6",

pages = "3873--3876",

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

issn = "1520-6149",

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

}

TY - JOUR

T1 - Mean-square analysis of normalized leaky adaptive filters

AU - Sayed, Ali H.

AU - Al-Naffouri, Tareq Y.

PY - 2001

Y1 - 2001

N2 - In this paper, we study leaky adaptive algorithms that employ a general scalar or matrix data nonlinearity. We perform mean-square analysis of this class of algorithms without imposing restrictions on the distribution of the input signal. In particular, we derive conditions on the step-size for stability, and provide closed form expressions for the steady-state performance.

AB - In this paper, we study leaky adaptive algorithms that employ a general scalar or matrix data nonlinearity. We perform mean-square analysis of this class of algorithms without imposing restrictions on the distribution of the input signal. In particular, we derive conditions on the step-size for stability, and provide closed form expressions for the steady-state performance.

UR - http://www.scopus.com/inward/record.url?scp=0034854282&partnerID=8YFLogxK

U2 - 10.1109/ICASSP.2001.940689

DO - 10.1109/ICASSP.2001.940689

M3 - Article

AN - SCOPUS:0034854282

SN - 1520-6149

VL - 6

SP - 3873

EP - 3876

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 -

Mean-square analysis of normalized leaky adaptive filters

Abstract

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this