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.
Classification of stochastic autogenerator signals by pattern recognition methods
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.
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