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On detection of the number of signals in presence of white noise. (English) Zbl 0617.62055
In the area of signal processing, it is of interest to detect the number of signals in presence of noise and to estimate the parameters of the signals. This problem is related to that of finding the multiplicity of the smallest eigenvalue of the covariance matrix of the observation vector. The methods used in this paper fall within the framework of the model selection procedures using information theoretic criteria the consistency of which is established also when the distribution underlying the observations is not necessarily complex Gaussian. The strong consistency of the estimates of the number of signals for different cases is obtained.
Reviewer: Fang Kai-Tai

MSC:
62H15Multivariate hypothesis testing
62H25Factor analysis and principal components; correspondence analysis
15A18Eigenvalues, singular values, and eigenvectors
62H99Multivariate analysis
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References:
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