NDLI: On estimating the number of signals

Content Provider	IEEE Xplore Digital Library
Author	Jie Yang Pinyuen Chen Tiee-Jian Wu
Copyright Year	2007
Description	Author affiliation: Syracuse Univ., Syracuse (Jie Yang)
Abstract	In this paper we apply model selection criteria in time series and regression analysis to the estimation of the number of signals in the MUSIC (multiple signal classification) method. We compare the following model selection (information) criteria: AIC, HQ, BIC, AICC, and the recently introduced WIC as the weighted average of AICC and BIC. The general form of the above information criteria consists of a log likelihood function expressed in terms of the eigenvalues of the covariance matrix and a unique penalty term. In our estimation procedure, the number of signals is obtained by minimizing each of the above criteria. A linear antenna array example is presented to compare the performance of the above model selection criteria in signal processing problem.
Starting Page	1132
Ending Page	1135
File Size	227650
Page Count	4
File Format	PDF
ISBN	9781424408771
DOI	10.1109/APS.2007.4395698
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-06-09
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Eigenvalues and eigenfunctions Multiple signal classification Covariance matrix Testing Statistical analysis Direction of arrival estimation Signal processing Statistical distributions Regression analysis Linear antenna arrays
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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