Existence and exponential stability of periodic solution for BAM neural networks with periodic coefficients and delays
In this paper, the existence and global exponential stability of the periodic solution are discussed for the bidirectional associative memory (BAM) neural networks with periodic coefficients and delays. Some new sufficient conditions for ascertaining the existence and global exponential stability of the periodic solution of such BAM neural networks are obtained by using the properties of nonsingular M-matrix, integral inequality analysis and a continuation theorem based on coincidence degree. These conclusions are presented not only in terms of systems parameters but also the period of the system and the mean values of decaying rates. Therefore, the results are fairly new. Moreover, some results from previous works are extended and improved. These results are helpful to design globally exponentially stable BAM networks and periodic oscillatory neural networks.
periodic solution bam neural networks coincidence degree nonsingular m-matrix