Adaptive bilinear filtering

Tamal Bose; Mei Qin Chen

Adaptive bilinear filtering

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

Abstract

The application of the Conjugate Gradient (CG) method for the identification of bilinear systems is investigated. An algorithm based on the CG method is developed for adaptive bilinear digital filtering. This algorithm outperforms the LMS and RLS methods in terms of speed of convergence. In this algorithm, the optimization is done over blocks of input and output data rather than a single pair of data. However, only one iteration and coefficient update is done for every sample of data. This, coupled with the fact that the CG method used here does not require a line search makes it very efficient in computation. A preconditioning technique is also studied to accelerate the convergence. Some examples are given to illustrate the efficiency of the method.

Original language	English (US)
Title of host publication	Proceedings - IEEE International Symposium on Circuits and Systems
Publisher	Publ by IEEE
Pages	48-51
Number of pages	4
ISBN (Print)	0780312813
State	Published - 1993
Externally published	Yes
Event	1993 IEEE International Symposium on Circuits and Systems - Chicago, IL, USA Duration: May 3 1993 → May 6 1993

Publication series

Name	Proceedings - IEEE International Symposium on Circuits and Systems
Volume	1
ISSN (Print)	0271-4310

Other

Other	1993 IEEE International Symposium on Circuits and Systems
City	Chicago, IL, USA
Period	5/3/93 → 5/6/93

ASJC Scopus subject areas

Electrical and Electronic Engineering

Cite this

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title = "Adaptive bilinear filtering",

abstract = "The application of the Conjugate Gradient (CG) method for the identification of bilinear systems is investigated. An algorithm based on the CG method is developed for adaptive bilinear digital filtering. This algorithm outperforms the LMS and RLS methods in terms of speed of convergence. In this algorithm, the optimization is done over blocks of input and output data rather than a single pair of data. However, only one iteration and coefficient update is done for every sample of data. This, coupled with the fact that the CG method used here does not require a line search makes it very efficient in computation. A preconditioning technique is also studied to accelerate the convergence. Some examples are given to illustrate the efficiency of the method.",

author = "Tamal Bose and Chen, {Mei Qin}",

year = "1993",

language = "English (US)",

isbn = "0780312813",

series = "Proceedings - IEEE International Symposium on Circuits and Systems",

publisher = "Publ by IEEE",

pages = "48--51",

booktitle = "Proceedings - IEEE International Symposium on Circuits and Systems",

note = "1993 IEEE International Symposium on Circuits and Systems ; Conference date: 03-05-1993 Through 06-05-1993",

}

TY - GEN

T1 - Adaptive bilinear filtering

AU - Bose, Tamal

AU - Chen, Mei Qin

PY - 1993

Y1 - 1993

N2 - The application of the Conjugate Gradient (CG) method for the identification of bilinear systems is investigated. An algorithm based on the CG method is developed for adaptive bilinear digital filtering. This algorithm outperforms the LMS and RLS methods in terms of speed of convergence. In this algorithm, the optimization is done over blocks of input and output data rather than a single pair of data. However, only one iteration and coefficient update is done for every sample of data. This, coupled with the fact that the CG method used here does not require a line search makes it very efficient in computation. A preconditioning technique is also studied to accelerate the convergence. Some examples are given to illustrate the efficiency of the method.

AB - The application of the Conjugate Gradient (CG) method for the identification of bilinear systems is investigated. An algorithm based on the CG method is developed for adaptive bilinear digital filtering. This algorithm outperforms the LMS and RLS methods in terms of speed of convergence. In this algorithm, the optimization is done over blocks of input and output data rather than a single pair of data. However, only one iteration and coefficient update is done for every sample of data. This, coupled with the fact that the CG method used here does not require a line search makes it very efficient in computation. A preconditioning technique is also studied to accelerate the convergence. Some examples are given to illustrate the efficiency of the method.

UR - http://www.scopus.com/inward/record.url?scp=0027151688&partnerID=8YFLogxK

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M3 - Conference contribution

AN - SCOPUS:0027151688

SN - 0780312813

T3 - Proceedings - IEEE International Symposium on Circuits and Systems

SP - 48

EP - 51

BT - Proceedings - IEEE International Symposium on Circuits and Systems

PB - Publ by IEEE

T2 - 1993 IEEE International Symposium on Circuits and Systems

Y2 - 3 May 1993 through 6 May 1993

ER -

Adaptive bilinear filtering

Abstract

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ASJC Scopus subject areas

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