Adaptive stack filtering by LMS and perceptron learning

Nirwan Ansari; Yuchou Huang; Jean Hsang Lin

doi:10.1109/ICASSP.1992.226412

Adaptive stack filtering by LMS and perceptron learning

Nirwan Ansari, Yuchou Huang, Jean Hsang Lin

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Scopus citations

Abstract

Stack filters are a class of sliding-window nonlinear digital filters that possess the weak superposition property (threshold decomposition) and the ordering property known as the stacking property. They have been demonstrated to be robust in suppressing noise. Two methods are introduced to adaptively configure a stack filter. One is by employing the least mean square (LMS) algorithm and the other is based on perceptron learning. Experimental results are presented to demonstrate the effectiveness of the methods for noise suppression.

Original language	English (US)
Title of host publication	ICASSP 1992 - 1992 International Conference on Acoustics, Speech, and Signal Processing
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	57-60
Number of pages	4
ISBN (Electronic)	0780305329
DOIs	https://doi.org/10.1109/ICASSP.1992.226412
State	Published - 1992
Event	1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1992 - San Francisco, United States Duration: Mar 23 1992 → Mar 26 1992

Publication series

Name	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	4
ISSN (Print)	1520-6149

Other

Other	1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1992
Country/Territory	United States
City	San Francisco
Period	3/23/92 → 3/26/92

All Science Journal Classification (ASJC) codes

Software
Signal Processing
Electrical and Electronic Engineering

Access to Document

10.1109/ICASSP.1992.226412

Cite this

Ansari, N., Huang, Y., & Lin, J. H. (1992). Adaptive stack filtering by LMS and perceptron learning. In ICASSP 1992 - 1992 International Conference on Acoustics, Speech, and Signal Processing (pp. 57-60). Article 226412 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 4). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.1992.226412

@inproceedings{314977e70cea41789e30937cff973989,

title = "Adaptive stack filtering by LMS and perceptron learning",

abstract = "Stack filters are a class of sliding-window nonlinear digital filters that possess the weak superposition property (threshold decomposition) and the ordering property known as the stacking property. They have been demonstrated to be robust in suppressing noise. Two methods are introduced to adaptively configure a stack filter. One is by employing the least mean square (LMS) algorithm and the other is based on perceptron learning. Experimental results are presented to demonstrate the effectiveness of the methods for noise suppression.",

author = "Nirwan Ansari and Yuchou Huang and Lin, {Jean Hsang}",

note = "Publisher Copyright: {\textcopyright} 1992 IEEE.; 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1992 ; Conference date: 23-03-1992 Through 26-03-1992",

year = "1992",

doi = "10.1109/ICASSP.1992.226412",

language = "English (US)",

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

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

pages = "57--60",

booktitle = "ICASSP 1992 - 1992 International Conference on Acoustics, Speech, and Signal Processing",

address = "United States",

}

Ansari, N, Huang, Y & Lin, JH 1992, Adaptive stack filtering by LMS and perceptron learning. in ICASSP 1992 - 1992 International Conference on Acoustics, Speech, and Signal Processing., 226412, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, vol. 4, Institute of Electrical and Electronics Engineers Inc., pp. 57-60, 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1992, San Francisco, United States, 3/23/92. https://doi.org/10.1109/ICASSP.1992.226412

Adaptive stack filtering by LMS and perceptron learning. / Ansari, Nirwan; Huang, Yuchou; Lin, Jean Hsang.
ICASSP 1992 - 1992 International Conference on Acoustics, Speech, and Signal Processing. Institute of Electrical and Electronics Engineers Inc., 1992. p. 57-60 226412 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 4).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Adaptive stack filtering by LMS and perceptron learning

AU - Ansari, Nirwan

AU - Huang, Yuchou

AU - Lin, Jean Hsang

PY - 1992

Y1 - 1992

N2 - Stack filters are a class of sliding-window nonlinear digital filters that possess the weak superposition property (threshold decomposition) and the ordering property known as the stacking property. They have been demonstrated to be robust in suppressing noise. Two methods are introduced to adaptively configure a stack filter. One is by employing the least mean square (LMS) algorithm and the other is based on perceptron learning. Experimental results are presented to demonstrate the effectiveness of the methods for noise suppression.

AB - Stack filters are a class of sliding-window nonlinear digital filters that possess the weak superposition property (threshold decomposition) and the ordering property known as the stacking property. They have been demonstrated to be robust in suppressing noise. Two methods are introduced to adaptively configure a stack filter. One is by employing the least mean square (LMS) algorithm and the other is based on perceptron learning. Experimental results are presented to demonstrate the effectiveness of the methods for noise suppression.

UR - http://www.scopus.com/inward/record.url?scp=77956837190&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77956837190&partnerID=8YFLogxK

U2 - 10.1109/ICASSP.1992.226412

DO - 10.1109/ICASSP.1992.226412

M3 - Conference contribution

AN - SCOPUS:77956837190

T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

SP - 57

EP - 60

BT - ICASSP 1992 - 1992 International Conference on Acoustics, Speech, and Signal Processing

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1992

Y2 - 23 March 1992 through 26 March 1992

ER -

Ansari N, Huang Y, Lin JH. Adaptive stack filtering by LMS and perceptron learning. In ICASSP 1992 - 1992 International Conference on Acoustics, Speech, and Signal Processing. Institute of Electrical and Electronics Engineers Inc. 1992. p. 57-60. 226412. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). doi: 10.1109/ICASSP.1992.226412

Adaptive stack filtering by LMS and perceptron learning

Abstract

Publication series

Other

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this