THE PRINCIPLE OF THE INFORMATION-DIVERGENCE MINIMUM IN THE PROBLEM OF SPECTRAL ANALYSIS OF THE RANDOM TIME SERIES UNDER THE CONDITION OF SMALL OBSERVATION SAMPLES

摘要

We consider the issue of small observation samples in the problem of spectral analysis of the random time series. It is proposed to solve the considered problem using the information-theoretic approach and a new algorithm based on the principle of minimum divergence of the cognominal spectral estimates yielded by the results of several independent observations in the Kullback-Leibler information metric. An example of a practical realization of the algorithm is considered and its asymptotic properties are studied.