Stabilizing effects of impulses in discrete-time delayed neural networks

IEEE Trans Neural Netw. 2011 Feb;22(2):323-9. doi: 10.1109/TNN.2010.2100084. Epub 2011 Jan 13.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Artificial Intelligence*
  • Cortical Synchronization / physiology
  • Electronic Data Processing / methods
  • Mathematical Computing*
  • Mathematical Concepts
  • Neural Networks, Computer*
  • Nonlinear Dynamics
  • Pattern Recognition, Automated / methods*
  • Reaction Time
  • Signal Processing, Computer-Assisted
  • Software Design
  • Time Factors