Published December 2019
| Version v1
Journal article
Synchronization of state-switching hopfield-type neural networks: A quantized level set approach
Creators
- 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.2019.08.016Additional 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.