Characterization of a cascade LMS predictor

DY Huang; Wen Su; A Nallanathan

Characterization of a cascade LMS predictor

DY Huang^*, Wen Su, A Nallanathan

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

5 Citations (Scopus)

Abstract

In this paper, an FIR cascade structure for adaptive linear prediction is studied in which each stage FIR filter is independently adapted using LMS algorithm. The theoretical analysis shows that the cascade performs a linear prediction in a way of successive refinement and each stage tries to obliterate the dominant mode of its input. Experimental results show that the performance of the cascade LMS predictor are in good agreement with our theoretical analysis.

Original language	English
Title of host publication	2005 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1-5
Place of Publication	NEW YORK
Publisher	IEEE
Pages	173-176
Number of pages	4
ISBN (Print)	0-7803-8874-7
Publication status	Published - 2005
Event	30th IEEE International Conference on Acoustics, Speech, and Signal Processing - Philadelphia, Panama Duration: 19 Mar 2005 → 23 Mar 2005

Publication series

Name	International Conference on Acoustics Speech and Signal Processing ICASSP
Publisher	IEEE
ISSN (Print)	1520-6149

Conference

Conference	30th IEEE International Conference on Acoustics, Speech, and Signal Processing
Country/Territory	Panama
Period	19/03/2005 → 23/03/2005

Cite this

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title = "Characterization of a cascade LMS predictor",

abstract = "In this paper, an FIR cascade structure for adaptive linear prediction is studied in which each stage FIR filter is independently adapted using LMS algorithm. The theoretical analysis shows that the cascade performs a linear prediction in a way of successive refinement and each stage tries to obliterate the dominant mode of its input. Experimental results show that the performance of the cascade LMS predictor are in good agreement with our theoretical analysis.",

author = "DY Huang and Wen Su and A Nallanathan",

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

publisher = "IEEE",

pages = "173--176",

booktitle = "2005 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1-5",

note = "30th IEEE International Conference on Acoustics, Speech, and Signal Processing ; Conference date: 19-03-2005 Through 23-03-2005",

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Huang, DY, Su, W & Nallanathan, A 2005, Characterization of a cascade LMS predictor. in 2005 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1-5. International Conference on Acoustics Speech and Signal Processing ICASSP, IEEE, NEW YORK, pp. 173-176, 30th IEEE International Conference on Acoustics, Speech, and Signal Processing, Panama, 19/03/2005.

Characterization of a cascade LMS predictor. / Huang, DY; Su, Wen; Nallanathan, A.
2005 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1-5. NEW YORK: IEEE, 2005. p. 173-176 (International Conference on Acoustics Speech and Signal Processing ICASSP).

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

TY - CHAP

T1 - Characterization of a cascade LMS predictor

AU - Huang, DY

AU - Su, Wen

AU - Nallanathan, A

PY - 2005

Y1 - 2005

N2 - In this paper, an FIR cascade structure for adaptive linear prediction is studied in which each stage FIR filter is independently adapted using LMS algorithm. The theoretical analysis shows that the cascade performs a linear prediction in a way of successive refinement and each stage tries to obliterate the dominant mode of its input. Experimental results show that the performance of the cascade LMS predictor are in good agreement with our theoretical analysis.

AB - In this paper, an FIR cascade structure for adaptive linear prediction is studied in which each stage FIR filter is independently adapted using LMS algorithm. The theoretical analysis shows that the cascade performs a linear prediction in a way of successive refinement and each stage tries to obliterate the dominant mode of its input. Experimental results show that the performance of the cascade LMS predictor are in good agreement with our theoretical analysis.

M3 - Conference paper

SN - 0-7803-8874-7

T3 - International Conference on Acoustics Speech and Signal Processing ICASSP

SP - 173

EP - 176

BT - 2005 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1-5

PB - IEEE

CY - NEW YORK

T2 - 30th IEEE International Conference on Acoustics, Speech, and Signal Processing

Y2 - 19 March 2005 through 23 March 2005

ER -

Characterization of a cascade LMS predictor

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