Efficient search algorithms for adaptive filtering

The performances of various adaptive filtering algorithms are evaluated based on their convergence rate, computational requirements, misadjustment, and numerical robustness. Improvements to the performance of adaptive filters by using new adaptation algorithms and by the use of recursive structur...

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Bibliographic Details
Main Author:	Zhao, Cheng.
Other Authors:	Abeysekera, Saman S.
Format:	Theses and Dissertations
Published:	2008
Subjects:	DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Online Access:	http://hdl.handle.net/10356/4022
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Institution:	Nanyang Technological University

id	sg-ntu-dr.10356-4022
record_format	dspace
spelling	sg-ntu-dr.10356-40222023-07-04T16:10:53Z Efficient search algorithms for adaptive filtering Zhao, Cheng. Abeysekera, Saman S. School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems The performances of various adaptive filtering algorithms are evaluated based on their convergence rate, computational requirements, misadjustment, and numerical robustness. Improvements to the performance of adaptive filters by using new adaptation algorithms and by the use of recursive structures are reported in the thesis. Master of Science 2008-09-17T09:42:47Z 2008-09-17T09:42:47Z 2004 2004 Thesis http://hdl.handle.net/10356/4022 Nanyang Technological University application/pdf
institution	Nanyang Technological University
building	NTU Library
continent	Asia
country	Singapore Singapore
content_provider	NTU Library
collection	DR-NTU
topic	DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
spellingShingle	DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems Zhao, Cheng. Efficient search algorithms for adaptive filtering
description	The performances of various adaptive filtering algorithms are evaluated based on their convergence rate, computational requirements, misadjustment, and numerical robustness. Improvements to the performance of adaptive filters by using new adaptation algorithms and by the use of recursive structures are reported in the thesis.
author2	Abeysekera, Saman S.
author_facet	Abeysekera, Saman S. Zhao, Cheng.
format	Theses and Dissertations
author	Zhao, Cheng.
author_sort	Zhao, Cheng.
title	Efficient search algorithms for adaptive filtering
title_short	Efficient search algorithms for adaptive filtering
title_full	Efficient search algorithms for adaptive filtering
title_fullStr	Efficient search algorithms for adaptive filtering
title_full_unstemmed	Efficient search algorithms for adaptive filtering
title_sort	efficient search algorithms for adaptive filtering
publishDate	2008
url	http://hdl.handle.net/10356/4022
_version_	1772828456984248320

Efficient search algorithms for adaptive filtering

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