具有时滞的双向联想记忆神经网络的全局渐近稳定性

Global Asymptotic Stability of Bidirectional Associative Memory Neural Networks with Delays

经网络的全局渐近稳定性．得出了保证神经网络平衡点稳定的几个充分条件，所得到的结论对于具有时滞的连续双向联想记忆神经网络的设计和应用都是很有意义的．

Bidirectional Associative Memory (BAM) models are two-myer heteroassociative networks. In the paper, the global asymptotic stability is studied for continuous bidirectional associative memory neural network's with signal transmission delays along the axon of neuron. Several sufficient conditions guaranteeing the neural network's global asymptotic stability are derived. The obtained results have important leading significance in the design and application of BAM.