An exponential evaluation for recurrent neural network with discrete delays

Authors

  • V. P. Martsenyuk The Department of Computer Science and Automatics of the University of Bielsko-Biala, Bielsko-Biala, Poland
  • A. S. Sverstiuk The Department of Medical Informatics of Ivan Horbachevsky Ternopil National Medical University, Ternopil, Ukraine https://orcid.org/0000-0001-8644-0776

DOI:

https://doi.org/10.20535/SRIT.2308-8893.2019.2.07

Keywords:

recurrent neural network, delay differential equations, exponential stability, Lyapunov functional

Abstract

The purpose of this study is to develop and apply a method for calculating the exponential fade rate for a model of a recurrent neural network based on discrete latency differential equations. An exponential estimate is obtained on the basis of the difference inequality for the Lyapunov function. An example of the exponential estimation for a model of a recurrent neural network with three neurons is presented.

Author Biographies

V. P. Martsenyuk, The Department of Computer Science and Automatics of the University of Bielsko-Biala, Bielsko-Biala

Vasyl Petrovich Martseniuk,

Doctor of Technical Sciences, a professor at the Department of Computer Science and Automatics of the University of Bielsko-Biala, Bielsko-Biala, Poland.

A. S. Sverstiuk, The Department of Medical Informatics of Ivan Horbachevsky Ternopil National Medical University, Ternopil

Andriy Stepanovich Sverstiuk,

Candidate of Technical Sciences, an associate professor at the Department of Medical Informatics of Ivan Horbachevsky Ternopil National Medical University, Ternopil, Ukraine.

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Published

2019-06-25

Issue

Section

Decision making and control in economic, technical, ecological and social systems