Detail publikace

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

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

Originální název

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

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

Functional differential equations; time-delay; neural networks

Autoři

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

Vydáno

27. 1. 2023

ISSN

0016-0032

Periodikum

JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS

Ročník

360

Číslo

1

Stát

Spojené státy americké

Strany od

301

Strany do

326

Strany počet

25

URL

https://www-webofscience-com.ezproxy.lib.vutbr.cz/wos/woscc/full-record/WOS:001088958900001

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"
}