Novel Existence and Stability Criteria of Periodic Solutions for Impulsive Delayed Neural Networks Via Coefficient Integral Averages

abstract

• 2016 Elsevier B.V. In this paper, an impulsive neural network with periodic coefficients and delayed time is firstly given, then the existence, uniqueness and exponential stability problems of periodic solutions for this system are further investigated. By means of the characteristic equation of delayed differential equations and impulsive differential equations, an impulsive delayed differential inequality with novel conditions are constructed. It can be used as an impulsive comparison system to deal with the existence and exponential stability problems. By utilizing the impulsive comparison system, Lyapunov functions and the fixed point theorem, we obtain the periodic solution's existence and exponential stability criteria. Finally, one numerical example and its simulations are given to illustrate the effectiveness of the theoretical results.

authors

• Huang, Tingwen

published proceedings

• NEUROCOMPUTING

author list (cited authors)

• Wang, H., Duan, S., Huang, T., Li, C., & Wang, L.

citation count

• 3

complete list of authors

• Wang, Huamin||Duan, Shukai||Huang, Tingwen||Li, Chuandong||Wang, Lidan

publication date

• December 2016

publisher

• Elsevier  Publisher

published in

• Neurocomputing  Journal

keywords

• Delayed Neural Networks
• Exponential Stability
• Impulsive Delayed Differential Inequality
• Integral Average Of Periodic Function
• Periodic Solution

Digital Object Identifier (DOI)

• 10.1016/j.neucom.2016.08.027

start page

• 587

end page

• 595

volume

• 216

URL

• http://dx.doi.org/10.1016/j.neucom.2016.08.027