Novel Criteria of ISS Analysis for Delayed Memristive Simplified Cohen–Grossberg BAM Neural Networks
Joint Authors
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-01-24
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
The memristor as the fourth circuit element, it can capture some key aspects of biological synaptic plasticity.
So, it is significant that the characteristic of memristors is considered in neural networks.
This paper investigates input-to-state stability (ISS) of a class of memristive simplified Cohen–Grossberg bidirectional associative memory (BAM) neural networks with variable time delays.
In the sense of Filippov solution, some novel sufficient criteria for ISS are obtained based on differential inclusions and differential inequalities; when the input is zero, the stability of the total system is state stable.
Furthermore, numerical simulations are illustrated to show the feasibility of our results.
American Psychological Association (APA)
Zhao, Yong& Ren, Shanshan. 2020. Novel Criteria of ISS Analysis for Delayed Memristive Simplified Cohen–Grossberg BAM Neural Networks. Complexity،Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1141545
Modern Language Association (MLA)
Zhao, Yong& Ren, Shanshan. Novel Criteria of ISS Analysis for Delayed Memristive Simplified Cohen–Grossberg BAM Neural Networks. Complexity No. 2020 (2020), pp.1-14.
https://search.emarefa.net/detail/BIM-1141545
American Medical Association (AMA)
Zhao, Yong& Ren, Shanshan. Novel Criteria of ISS Analysis for Delayed Memristive Simplified Cohen–Grossberg BAM Neural Networks. Complexity. 2020. Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1141545
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1141545