Global Exponential Stability of Bam Neural Networks with Varying Coefficient and Impulses
Xiaojian Hu · Journal of Biomathematics · 2007
In this paper,some sufficient conditions ensuring existence,uniqueness, and global exponential stability of the equilibrium point of a class of two-layer het- eroassociative networks called bidirectional associative memory(BAM) networks with impulses are obtained,which makes full use of Lipschitzian activation functions without assuming their bounded,monotonicity or differentiability and subjected to impulsive state displacements at fixed instants of time.An illustrative example is to demonstrate the effectiveness of the obtained results.