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ISSN 2542-1905 (Online)


For citation:

Vasin D. J., Gromov V. P. Classification of stochastic autogenerator signals by pattern recognition methods. Izvestiya VUZ. Applied Nonlinear Dynamics, 1994, vol. 2, iss. 2, pp. 57-63.

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Russian
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Article
UDC: 
621.391.193 + 531.391

Classification of stochastic autogenerator signals by pattern recognition methods

Autors: 
Vasin Dmitrij Jurevich, Institute of Applied Mathematics and Cybernetics. Nizhny Novgorod state University
Gromov Vladimir Petrovich, Institute of Applied Mathematics and Cybernetics. Nizhny Novgorod state University
Abstract: 

In this research a new technology for estimating a state of the nonlinear dynamical system in which chaos can be observed has been studied. The technology lies upon sequential employment of pattern recognition methods. On the basis of this technology a system of classifying stochastic generator (SG) signals with 1.5 degrees of freedom has been synthesized. 
The suggested approach for stochastic generator state estimation makes possible to solve efficiently the following problems of stochastic generator signal processing:  
— choosing on a substantial basis parameters and algorithms for amplitude—time quantification and for segmenting SG signals ; 
— designing the systems for compact representation of SG signal fragments ; 
— designing the PC-based banks of training data ; 
— deriving the systems of decision rules for SG signal classification; 
— synthesizing the systems for classifying SG states.

Key words: 
Acknowledgments: 
In conclusion, the authors express their deep gratitude to V.D. Shalfeev and N.F. Rulkov for help and support during this work. The work was carried out with financial support from the Russian Foundation for Basic Research (project 93-02-15424).
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Received: 
29.04.1994
Accepted: 
12.07.1994
Published: 
08.08.1994