Synchronization of neural networks with stochastic perturbation via aperiodically intermittent control. Academic Article

abstract

• In this paper, the synchronization problem for neural networks with stochastic perturbation is studied with intermittent control via adaptive aperiodicity. Under the framework of stochastic theory and Lyapunov stability method, we develop some techniques of intermittent control with adaptive aperiodicity to achieve the synchronization of a class of neural networks, modeled by stochastic systems. Some effective sufficient conditions are established for the realization of synchronization of the underlying network. Numerical simulations of two examples are provided to illustrate the theoretical results obtained in the paper.

authors

• Huang, Tingwen

published proceedings

• Neural Netw

author list (cited authors)

• Zhang, W., Li, C., Huang, T., & Xiao, M.

citation count

• 85

complete list of authors

• Zhang, Wei||Li, Chuandong||Huang, Tingwen||Xiao, Mingqing

publication date

• November 2015

publisher

• Elsevier  Publisher

published in

• Neural Networks  Journal

keywords

• Adaptive Control
• Algorithms
• Aperiodically Intermittent Control
• Neural Networks
• Neural Networks, Computer
• Stochastic Perturbation
• Stochastic Processes
• Synchronization

PubMed Central ID

• 26319051

Digital Object Identifier (DOI)

• 10.1016/j.neunet.2015.08.002

start page

• 105

end page

• 111

volume

• 71

URL

• http://dx.doi.org/10.1016/j.neunet.2015.08.002