Abstract
In this paper, we analyze the stability of distributed Hopfield neural networks. Distributed parameter Hopfield neural networks model is established by PDEs so state space of the controlled system belongs infinity dimensions, which is different from ODEs and DAEs models. Reaction-Diffusion Hopfield neural networks model is a new class of net systems which exist widely in control science, intelligent computation, cells of neurology and biology mathematica. Most of papers about Hopfield neural networks apply average Lyapunov function and M-matrix theory to study stability. Now, we use operator spectral theory to obtain stability of the system, which does not need complex calculation. At last, we make some simulations verify our criterions.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 35th Chinese Control Conference, CCC 2016 |
| Publisher | IEEE |
| Pages | 1447-1452 |
| Number of pages | 6 |
| Volume | 2016-August |
| ISBN (Electronic) | 9789881563910 |
| DOIs | |
| Publication status | Published - 26 Aug 2016 |
| MoE publication type | A4 Conference publication |
| Event | Chinese Control Conference - Chengdu, China Duration: 27 Jul 2016 → 29 Jul 2016 Conference number: 35 http://ccc2016.swjtu.edu.cn/ |
Conference
| Conference | Chinese Control Conference |
|---|---|
| Abbreviated title | ccc2016 |
| Country/Territory | China |
| City | Chengdu |
| Period | 27/07/2016 → 29/07/2016 |
| Internet address |
Keywords
- Hopfield Neural Network
- Operator Spectral Theory
- Reaction-Diffusion System
- Stability