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Detection of signals by information theoretic criteria

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2 Author(s)
M. Wax ; Stanford University, Stanford, CA, USA ; T. Kailath

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.

Published in:

IEEE Transactions on Acoustics, Speech, and Signal Processing  (Volume:33 ,  Issue: 2 )