DocumentCode
1105615
Title
Detection of signals by information theoretic criteria
Author
Wax, Mati ; Kailath, Thomas
Author_Institution
Stanford University, Stanford, CA, USA
Volume
33
Issue
2
fYear
1985
fDate
4/1/1985 12:00:00 AM
Firstpage
387
Lastpage
392
Abstract
A new approach is presented to the problem of detecting the number of signals in a multichannel time-series, based on the application of the information theoretic criteria for model selection introduced by Akaike (AIC) and by Schwartz and Rissanen (MDL). Unlike the conventional hypothesis testing based approach, the new approach does not requite any subjective threshold settings; the number of signals is obtained merely by minimizing the AIC or the MDL criteria. Simulation results that illustrate the performance of the new method for the detection of the number of signals received by a sensor array are presented.
Keywords
Additive noise; Array signal processing; Backscatter; Covariance matrix; Sensor arrays; Sensor phenomena and characterization; Signal detection; Signal processing; Testing; Transient response;
fLanguage
English
Journal_Title
Acoustics, Speech and Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
0096-3518
Type
jour
DOI
10.1109/TASSP.1985.1164557
Filename
1164557
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