Publication detail

Exponential stability criteria for linear neutral systems with applications to neural networks of neutral type

BEREZANSKY, L. DIBLÍK, J. SVOBODA, Z. ŠMARDA, Z.

Original Title

Exponential stability criteria for linear neutral systems with applications to neural networks of neutral type

Type

journal article in Web of Science

Language

English

Original Abstract

Linear neutral vector equations are considered on interval [0, infinity). Here x = (x(1),...,x(n))(T), m is a positive integer, the entries of matrices A(l), l = 0,...,m, P, and the delays h(k), k = 0,...,m, g are assumed to be Lebesgue measurable functions. New explicit criteria are derived on uniform exponential stability. Comparisons are made and discussed based on an overview of the existing results. An application is presented to local exponential stability of non-autonomous neural network models of neutral type.

Keywords

Functional differential equations; time-delay; neural networks

Authors

BEREZANSKY, L.; DIBLÍK, J.; SVOBODA, Z.; ŠMARDA, Z.

Released

27. 1. 2023

ISBN

0016-0032

Periodical

JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS

Year of study

360

Number

1

State

United States of America

Pages from

301

Pages to

326

Pages count

25

URL

BibTex

@article{BUT185104,
  author="Leonid {Berezansky} and Josef {Diblík} and Zdeněk {Svoboda} and Zdeněk {Šmarda}",
  title="Exponential stability criteria for linear neutral systems with applications to neural networks of neutral type",
  journal="JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS",
  year="2023",
  volume="360",
  number="1",
  pages="301--326",
  doi="10.1016/j.jfranklin.2022.11.012",
  issn="0016-0032",
  url="https://www-webofscience-com.ezproxy.lib.vutbr.cz/wos/woscc/full-record/WOS:001088958900001"
}