Abstract
The stability of Hopfield neural networks with fixed-time impulses has been intensively investigated in recent years. However, few existing publications addressed the stability of delayed neural networks with variable-time impulses. In this paper, we consider the case of variable-time impulses and attempt to establish the general stability criteria. It shows that the proposed results can also be applied to the case of fixed-time impulses, which provide a new stability condition for the case of fixed-time impulses. To illustrate the effectiveness of our theoretical results, numerical examples and simulations are also presented. © 2011 Springer-Verlag London Limited.
| Original language | English |
|---|---|
| Pages (from-to) | 195-202 |
| Journal | Neural Computing and Applications |
| Volume | 22 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 1 Jan 2013 |
| Externally published | Yes |
Bibliographical note
Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].Funding
The work described in this paper was partially supported by the Fundamental Research Funds for the Central Universities of China (Project No. CDJZR10 18 55 01) and National Natural Science Foundation of China (Grant No.60974020).
Research Keywords
- Hopfield neural network (HNN)
- Stability
- Time delays
- Variable-time impulse
Fingerprint
Dive into the research topics of 'Stability of Hopfield neural networks with time delays and variable-time impulses'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver