title: Global exponential stability of hybrid bidirectional associative memory neural networks with discrete delays.
abstract: In this paper, the dynamical characteristics of hybrid bidirectional associative memory neural networks with constant transmission delays are investigated. Without assuming symmetry of synaptic connection weights and monotonicity and differentiability of activation functions, Halanay-type inequalities (which are different from the approach of constructing Lyapunov functionals) are employed to derive the delay-independent sufficient conditions under which the networks converge exponentially to the equilibria associated with temporally uniform external inputs. Our results are less conservative and restrictive than previously known results.
authors.affiliation: Department of Computer Science and Engineering, Chongqing University, People's Republic of China. xfliao@cqu.edu.cn
authors.forename: Xiaofeng
authors.initials: X
authors.lastname: Liao
authors.forename: Kwok-Wo
authors.initials: KW
authors.lastname: Wong
mesh_terms: D000465:Algorithms; D008568:Memory; D015233:Models, Statistical; D008962:Models, Theoretical; D009415:Nerve Net