MODEL AND METHOD OF A MULTI-LEVEL RECOGNITION SYSTEM CONSTRUCTION
Journal Title: Вісник Кременчуцького національного університету імені Михайла Остроградського - Year 2017, Vol 1, Issue 107
Abstract
Purpose. To consider existing approaches to the construction of recognition systems. The task of pattern recognition can be solved step by step, if in the analysis of data, hierarchical structures are distinguished in the feature space. A method has been proposed for synthesizing a multilevel architecture of a neural network system for solving diagnostic problems. Results. The method is based on the nesting of microclusters, clusters and macroclusters in the feature space. The second condition for splitting the recognition process into stages is the decomposition of characteristics set into unifying and separating subsets. With the help of a unifying subset of features, clusters are formed within the macrocluster at the first stage. In the second stage, using a separating subset of features within clusters, microclusters are distinguished, which are groups of objects with certain properties. Practical value. A two-level recognition system, obtained as a result of synthesis based on the developed method, is logically transparent and allows increasing recognition accuracy in comparison with classical perceptrons on the same set of features. The developed model and method of synthesis of a neural network multilevel system is a simple and effective means of solving practical problems of diagnostics and image recognition.
Authors and Affiliations
I. Shevchenko, N. Shkarupa, М. Gonchar
Keywords
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