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Synthesis fundamentals of classifiers for technical systems of patterns recognition with the use of human’s models of emotional processes

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Category: Information technologies, systems analysis and administration

Last Updated on 04 June 2015

Published on 29 March 2015

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Authors:

A.S. Meniailenko, Dr. Sci. (Tech.), Professor, Luhansk Taras Shevchenko National University, Vice Rector, Luhansk, Ukraine

O.I. Zakhozhay, Cand.Sci. (Tech.), Associate Professor, Donbass State Technical University, Senior Lecturer of the Electronic Systems Department, Alchevsk, Ukraine

Abstract:

Purpose. Development of the emotional processes application method, by analogy with human, in technical systems of patterns recognition. It gives possibility to enhance the reliability and reduce the time spent on the classification.

Methodology. We have analyzed the appropriateness of use of different emotional processes in design of classifiers of technical systems of patterns recognition. The proposed information model of human memory has been generalized for the technical intelligent systems; it was based on the Atkinson-Shifrin concept. We suggest using of emotional components in the classification algorithms for the combined systems of patterns recognition. We have determined the ways of further investigations concerning the improvement of the classifiers design methods with the use of emotional processes.

Findings. Comparative analysis of human-made intelligent systems with human intelligence showed the classification results discrepancy connected with the additional emotional aspects which are not considered. The proposed information model is a generalization of the Atkinson-Shifrin model for the technical recognition systems. To make the recognition systems similar to the cognitive human apparatus, we have proposed improvement of memory model through the introduction of characteristics describing the emotional processes. This allows ranking signs for their placement in short-term memory. We have proposed to determine quantitative estimates of emotional stats as a differential of the objective function for each individual information channel. We have found out that the use of combined systems of patterns recognition requires comparison of emotional processes on various information channels.

Originality. We have proposed the information model of human memory that is a generalization of the Atkinson-Shifrin model for the technical recognition systems with characteristics describing the emotional processes, and the method for quantitative estimation of the level of emotional processes in technical systems of patterns recognition. We have defined the concept of emotional processes use in combined systems of patterns recognition.

Practical value. The use of proposed solutions allows implementing rational aggregate of emotional components in the technical systems of patterns recognition. For defined conditions it allows us to increase the classification accuracy and reduce the time complexity of this process.

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