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

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

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Abstract

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

Item Type:	Article (Journal)
Additional Information:	2470/6955
Subjects:	T Technology > T Technology (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Mechatronics Engineering
Depositing User:	Prof Momoh-Jimoh Salami
Date Deposited:	09 May 2013 09:13
Last Modified:	13 Dec 2013 10:04
URI:	http://irep.iium.edu.my/id/eprint/6955

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