Published December 2019 | Version v1
Journal article

Synchronization of state-switching hopfield-type neural networks: A quantized level set approach

  • 1. School of Science, Jimei University, Xiamen, 361021 (China)

Description

This paper presents the quantized synchronization of state-switching hopfield-type neural networks (SSHNNs) with delays. Due to a quantized controller with saturation, some unified synchronization criterion for SSHNNs with discrete delays and distributed delays are obtained. The quantized adaptive saturation controller (QASC) relies only on the quantized level sets, and hence greatly reduces the control cost and improves the practicability of the SSHNNs synchronization principle. The obtained results are new and improve the existing ones. Finally, numerical examples are given to demonstrate the correctness of our theoretical results.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.chaos.2019.08.016

Additional details

Identifiers

DOI
10.1016/j.chaos.2019.08.016;
PII
S0960077919303261;

Publishing Information

Journal Title
Chaos, Solitons and Fractals
Journal Volume
129
Journal Page Range
p. 16-24
ISSN
0960-0779

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
54120466
Subject category
S97: MATHEMATICAL METHODS AND COMPUTING;
Descriptors DEI
CONTROL; NEURAL NETWORKS; SYNCHRONIZATION

Optional Information

Copyright
Copyright (c) 2019 Elsevier Ltd. All rights reserved.