Abstract
In this paper, an impulsive Cohen-Grossberg bidirectional associative neural network with both time-varying and distributed delays is examined. Novel sufficient conditions for deriving stability with a desired rate, including the exponential one, are obtained. We consider a large class of admissible kernels encompassing the existing ones. Our findings cover the existing stability results in the literature. Finally, a numerical example is given for the validation of the theoretical outcomes.
| Original language | English |
|---|---|
| Pages (from-to) | 709-728 |
| Number of pages | 20 |
| Journal | Journal of Experimental and Theoretical Artificial Intelligence |
| Volume | 35 |
| Issue number | 5 |
| DOIs | |
| State | Published - 2023 |
Bibliographical note
Publisher Copyright:© 2021 Informa UK Limited, trading as Taylor & Francis Group.
Keywords
- Cohen-Grossberg
- General stability
- bidirectional associative memory
- distributed delay
- impulse
- time-varying delay
ASJC Scopus subject areas
- Software
- Theoretical Computer Science
- Artificial Intelligence
Fingerprint
Dive into the research topics of 'Stability for a retarded impulsive Cohen–Grossberg BAM neural network system'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver