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MULTILEVEL NON-PARAMETRICAL SYSTEMS OF PATTERN RECOGNITION

By Boris Valerievich Shcherbakov and The Krasnoyarsky Regional Affilial of Agrpprombank (Russian Federation)

Abstract

The investigation objects are the multilevel algorithms for pattern recognition using the non-parametrical probability density evaluation obtained on base of the learning sampling. The aim is to develop the methods for constructing multilevel non-parametrical systems of the pattern recognition on base of the consecutive procedures of making solutions. The synthesis and analysis methods of the multilevel non-parametrical systems of pattern recognition permitting to increase the efficiency in the solution of the classification problems have been developed. The asymptotic properties of the non-parametrical evaluation in the error of the pattern recognition and limitation for the indices of the efficiency in the consecutive procedures of making solutions have been determined. The algorithm for formation of the informative sign sets used in the problem on the choice of the rational structure for multilevel systems of pattern reconification has been proposed. The software of the multilevel non-parametrical pattern recognition systems which have been used at development of the information system for forecasting of the meteorotrophic complications in the cardiovascular diseases taking helio factors into consideration and program complex for determination of the risk in development of the cardiovascular diseases have been developed.Available from VNTIC / VNTIC - Scientific & Technical Information Centre of RussiaSIGLERURussian Federatio

Topics: 09K - Pattern recognition, image processing, 05T - Health services, health administration, community care services, MULTILEVEL NON-PARAMETRICAL SYSTEMS, PATTERN RECOGNITION
Year: 1997
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Provided by: OpenGrey Repository
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