Stability conditions for discrete hopfield neural networks with delay

Authors:
Run-Nian Ma;Guo-Qiang Bai
Affiliations:
School of Science, Xi’an Jiaotong University, Xi’an, China;Institute of Microelectronics, Tsinghua University, Beijing, China
Venue:
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
Year:
2006

Citing 3
Cited 0

Antisymmetrical neural networks

Discrete Applied Mathematics
Dynamic behavior analysis of discrete neural networks with delay

ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part I
New stability conditions for Hopfield networks in partial simultaneous update mode

IEEE Transactions on Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

The stability of discrete Hopfield neural networks with delay is mainly studied by the use of the state transition equation and the energy function, and some results on the stability are given. The sufficient conditions for the networks with delay converging towards a limit cycle with length 4 are presented. Also, one condition ensuring the network with delay having neither a stable state nor a limit cycle with length 2 is given. The obtained results here partially extend some existing results on stability of discrete Hopfield neural network with delay and without delay.