Further results on robust stability of bidirectional associative memory neural networks with norm-bounded uncertainties

Abstract

Abstract In this paper, we have a further study about global robust stability of dynamical bidirectional associative memory (BAM) neural networks with norm-bounded uncertainties. By introducing four new upper bound norms for the interconnection matrices of the neural networks and constructing a suitable Lyapunov functional, several new criteria on global robust stability are established. The obtained results can be easily verified as they can be expressed in terms of the network parameters only. In comparison with the results reported in the literature, the proposed approach leads to results with less restrictive conditions. Two numerical examples are also worked through to illustrate our results.