Performance evaluation of music and minimum norm Eigenvector Algorithms in resolving noisy multiexponential signals

Abstract—Eigenvector methods are gaining increasing acceptance in the area of spectrum estimation. This paper presents a successful attempt at testing and evaluating the performance of two of the most popular types of subspace techniques in determining the parameters of multiexponential signals...

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Main Authors:	Jibia, Abdussamad Umar, Salami, Momoh Jimoh Eyiomika
Format:	Article
Language:	English
Published:	World Academy of Science, Engineering and Technology (W A S E T) 2007
Subjects:	T Technology (General)
Online Access:	http://irep.iium.edu.my/6955/ http://irep.iium.edu.my/6955/1/Performance_Evaluation_of_Music_and_Minimum.pdf

id	iium-6955
recordtype	eprints
spelling	iium-69552013-12-13T02:04:35Z http://irep.iium.edu.my/6955/ Performance evaluation of music and minimum norm Eigenvector Algorithms in resolving noisy multiexponential signals Jibia, Abdussamad Umar Salami, Momoh Jimoh Eyiomika T Technology (General) Abstract—Eigenvector methods are gaining increasing acceptance in the area of spectrum estimation. This paper presents a successful attempt at testing and evaluating the performance of two of the most popular types of subspace techniques in determining the parameters of multiexponential signals with real decay constants buried in noise. In particular, MUSIC (Multiple Signal Classification) and minimum-norm techniques are examined. It is shown that these methods perform almost equally well on multiexponential signals with MUSIC displaying better defined peaks World Academy of Science, Engineering and Technology (W A S E T) 2007 Article PeerReviewed application/pdf en http://irep.iium.edu.my/6955/1/Performance_Evaluation_of_Music_and_Minimum.pdf Jibia, Abdussamad Umar and Salami, Momoh Jimoh Eyiomika (2007) Performance evaluation of music and minimum norm Eigenvector Algorithms in resolving noisy multiexponential signals. World Academy of Science, Engineering and Technology, 32. pp. 24-28. ISSN 1307-6884
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	T Technology (General)
spellingShingle	T Technology (General) Jibia, Abdussamad Umar Salami, Momoh Jimoh Eyiomika Performance evaluation of music and minimum norm Eigenvector Algorithms in resolving noisy multiexponential signals
description	Abstract—Eigenvector methods are gaining increasing acceptance in the area of spectrum estimation. This paper presents a successful attempt at testing and evaluating the performance of two of the most popular types of subspace techniques in determining the parameters of multiexponential signals with real decay constants buried in noise. In particular, MUSIC (Multiple Signal Classification) and minimum-norm techniques are examined. It is shown that these methods perform almost equally well on multiexponential signals with MUSIC displaying better defined peaks
format	Article
author	Jibia, Abdussamad Umar Salami, Momoh Jimoh Eyiomika
author_facet	Jibia, Abdussamad Umar Salami, Momoh Jimoh Eyiomika
author_sort	Jibia, Abdussamad Umar
title	Performance evaluation of music and minimum norm Eigenvector Algorithms in resolving noisy multiexponential signals
title_short	Performance evaluation of music and minimum norm Eigenvector Algorithms in resolving noisy multiexponential signals
title_full	Performance evaluation of music and minimum norm Eigenvector Algorithms in resolving noisy multiexponential signals
title_fullStr	Performance evaluation of music and minimum norm Eigenvector Algorithms in resolving noisy multiexponential signals
title_full_unstemmed	Performance evaluation of music and minimum norm Eigenvector Algorithms in resolving noisy multiexponential signals
title_sort	performance evaluation of music and minimum norm eigenvector algorithms in resolving noisy multiexponential signals
publisher	World Academy of Science, Engineering and Technology (W A S E T)
publishDate	2007
url	http://irep.iium.edu.my/6955/ http://irep.iium.edu.my/6955/1/Performance_Evaluation_of_Music_and_Minimum.pdf
first_indexed	2023-09-18T20:16:08Z
last_indexed	2023-09-18T20:16:08Z
_version_	1777407799673749504

Performance evaluation of music and minimum norm Eigenvector Algorithms in resolving noisy multiexponential signals

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