Dynamic behavior of discrete hopfield neural networks with time-delay

The dynamic behavior of recurrent neural networks is not only known to be one of the mostly basic problems, but also known to be bases of the network's widely various applications. The discrete Hopfield neural network with delay is an extension of the famous discrete Hopfield neural networks. The parallel stability of discrete Hopfield neural networks with delay is mainly investigated by the use of the state transition equation and the energy function. Some sufficient criteria are given to ensure the networks with delay converging towards a stable state in parallel updating mode. The established results here extend the previous results on stability of discrete Hopfield neural network both without delay and with delay.