Impulsive stabilization and synchronization of Hopfield-type neural networks with impulse time window Academic Article

abstract

• 2015, The Natural Computing Applications Forum. This paper studies the problem of global exponential stabilization and synchronization for impulsive Hopfield-type neural networks with impulse time window. By using the stability theory of impulsive dynamical systems, some sufficient conditions guaranteeing the global exponential stabilization and synchronization of Hopfield-type NNs are derived. The main innovation embodies that the impulsive instants are no longer limited at fixed instants, but suggested to be at some certain time intervals, named by impulse time windows. We shall show that impulses occurring randomly in impulse time windows can still stabilize and/or synchronize the considered neural networks under certain suitable assumptions. Two numerical examples are also given to illustrate the effectiveness of theoretical results.

authors

• Huang, Tingwen

published proceedings

• NEURAL COMPUTING & APPLICATIONS

author list (cited authors)

• Zhou, Y., Li, C., Huang, T., & Wang, X.

citation count

• 30

complete list of authors

• Zhou, Yinghua||Li, Chuandong||Huang, Tingwen||Wang, Xin

publication date

• April 2017

publisher

• Springer Nature  Publisher

published in

• Neural Computing and Applications  Journal

keywords

• Hopfield-type Neural Networks (nns)
• Impulse Time Window
• Impulsive Stabilization
• Synchronization

Digital Object Identifier (DOI)

• 10.1007/s00521-015-2105-7

start page

• 775

end page

• 782

volume

• 28

issue

• 4

URL

• http://dx.doi.org/10.1007/s00521-015-2105-7