Published February 2021 | Version v1
Journal article

Almost periodic dynamics in a new class of impulsive reaction–diffusion neural networks with fractional-like derivatives

  • 1. Department of Mathematics, Burgas "Prof. Dr. Assen Zlatarov" University, Burgas (Bulgaria)
  • 2. Department of Mathematics, University of Texas at San Antonio, San Antonio, TX (United States)
  • 3. S.P. Timoshenko Institute of Mechanics, NAS of Ukraine, Kiev (Ukraine)
  • 4. Department of Machine Elements and Non-metallic Constructions, Technical University of Sofia, Sofia (Bulgaria)

Description

This paper introduces a new class of reaction–diffusion neural networks with impulses and recently defined fractional-like derivatives. Sufficient conditions for the existence-uniqueness of almost periodic solutions are proposed by constructing suitable Lyapunov-like functions. Our results are new and contribute to the development of the knowledge on impulsive fractional-like evolution models. Finally, as an example a fractional-like generalization of a reaction-diffusion model in epidemiology that simulates the hepatitis B virus (HBV) infection with spatial dependence is considered.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.chaos.2020.110647

Additional details

Identifiers

DOI
10.1016/j.chaos.2020.110647;
PII
S0960077920310389;

Publishing Information

Journal Title
Chaos, Solitons and Fractals
Journal Volume
143
Journal Page Range
vp.
ISSN
0960-0779

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
53098917
Subject category
S97: MATHEMATICAL METHODS AND COMPUTING;
Descriptors DEI
LYAPUNOV METHOD; MATHEMATICAL SOLUTIONS; NEURAL NETWORKS; SPACE DEPENDENCE
Descriptors DEC
CALCULATION METHODS

Optional Information

Copyright
Copyright (c) 2021 Elsevier Ltd. All rights reserved.