Global exponential stability of BAM neural networks with distributed delays and impulses

Convergence dynamics of bi-directional associative memory (BAM) neural networks with continuously distributed delays and impulses are discussed. Without assuming the differentiability and the monotonicity of the activation functions and symmetry of synaptic interconnection weights, sufficient conditions to guarantee the existence and global exponential stability of a unique equilibrium are given.