title: Stabilizing effects of impulses in discrete-time delayed neural networks.
abstract: This brief studies the global exponential stability of the equilibrium point of discrete-time delayed Hopfield neural networks (DHNNs) with impulse effects by using difference inequalities. We shall consider the stabilizing effects of impulses when the corresponding impulse-free DHNN is even not asymptotically stable. The obtained results characterize the aggregated effects of impulses and deviation of the impulse-free DHNN from its equilibrium point on the exponential stability of the whole system. It is shown that, because of effects of impulses, the impulsive discrete-time DHNN may be exponentially stable even if the evolution of impulse-free component deviates from its equilibrium point exponentially.
authors.affiliation: College of Computers, Chongqing University, Chongqing 400030, China. licd@cqu.edu.cn
authors.forename: Chuandong
authors.initials: C
authors.lastname: Li
authors.forename: Sichao
authors.initials: S
authors.lastname: Wu
authors.forename: Gang Gary
authors.initials: GG
authors.lastname: Feng
authors.forename: Xiaofeng
authors.initials: X
authors.lastname: Liao
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003344:Cortical Synchronization / Q000502:physiology; D001330:Electronic Data Processing / Q000379:methods; D008432:Mathematical Computing; D055641:Mathematical Concepts; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D010363:Pattern Recognition, Automated / Q000379:methods*; D011930:Reaction Time; D012815:Signal Processing, Computer-Assisted; D012985:Software Design; D013997:Time Factors