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Radiophysics and Quantum Electronics

, Volume 58, Issue 5, pp 373–379 | Cite as

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

  • V. V. Savchenko
Article

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.

Keywords

Power Spectral Density Speech Signal Information Divergence Speech Database Accuracy Index 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Nizhny Novgorod State Linguistic UniversityNizhny NovgorodRussia

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