pth input-to-state stability of stochastic bidirectional associative memory neural networks with infinite delays

In this paper, bidirectional associative memory neural networks (BAMNNs) with infinite delays under the influence of Brownian motion or Markovian switching are investigated respectively. By utilizing Itô formula and constructing new Halanay differential inequalities, two sufficient conditions ensuring the pth input-to-state stability (p-ISS) of the neural networks are obtained. A numerical example is given to illustrate the efficiency of the derived results.