Robust stability of stochastic fuzzy delayed neural networks with impulsive time window. Academic Article

abstract

• The urgent problem of impulsive moments which cannot be determined in advance brings new challenges beyond the conventional impulsive systems theory. In order to solve this problem, the novel concept of impulsive time window is proposed in this paper. And the stability problem of stochastic fuzzy uncertain delayed neural networks with impulsive time window is investigated. By combining the discretized Lyapunov function approach with mathematical induction method, several novel and easy-to-check sufficient conditions concerning the impulsive time window are derived to ensure that the model considered here is exponentially stable in mean square. Numerical simulations are presented to further demonstrate the effectiveness of the proposed stability criterion.

authors

• Huang, Tingwen

published proceedings

• Neural Netw

author list (cited authors)

• Wang, X., Yu, J., Li, C., Wang, H., Huang, T., & Huang, J.

citation count

• 35

complete list of authors

• Wang, Xin||Yu, Junzhi||Li, Chuandong||Wang, Hui||Huang, Tingwen||Huang, Junjian

publication date

• July 2015

publisher

• Elsevier  Publisher

published in

• Neural Networks  Journal

keywords

• Algorithms
• Fuzzy Logic
• Impulsive Time Window
• Models, Neurological
• Neural Networks, Computer
• Nonlinear Dynamics
• Robust Stability
• Stochastic Fuzzy Neural Networks
• Stochastic Processes
• Systems Theory
• Uncertainty

PubMed Central ID

• 25897509

Digital Object Identifier (DOI)

• 10.1016/j.neunet.2015.03.010

start page

• 84

end page

• 91

volume

• 67

URL

• http%3A%2F%2Fdx.doi.org%2F10.1016%2Fj.neunet.2015.03.010