In this paper, the global exponential stability and periodicity of a class of recurrent neural networks with time delays are addressed by using Lyapunov functional method and inequality techniques. The delayed neural network includes the well-known Hopfield neural networks, cellular neural networks, and bidirectional associative memory networks as its special cases. New criteria are found to ascertain the global exponential stability and periodicity of the recurrent neural networks with time delays, and are also shown to be different from and improve upon existing ones.
|Number of pages||12|
|Journal||IEEE Transactions on Circuits and Systems I: Regular Papers|
|Publication status||Published - May 2005|
- Lyapunov method
- Recurrent neural networks
- Time delay