A design method of criteria for detecting the number of superimposed signals

Summary form only given. The paper proposes a novel method for designing the criteria for detecting the number of signals superimposed in a multichannel time-series, based on the maximum likelihood statistics for observation models. The proposed method can be applied to the case of a small number of observation samples available, while conventional methods based on information criteria have difficulties because of the asymptotic stochastic properties for the maximum likelihood used in their formulation. Finally, simulation results are shown to demonstrate the validity of the proposed method.