Effects of variable-time impulses on global exponential stability of Cohen-Grossberg neural networks Academic Article

abstract

• We investigate the global exponential stability of CohenGrossberg neural networks (CGNNs) with variable moments of impulses using B-equivalence method. Under certain conditions, we show that each solution of the considered system intersects each surface of discontinuity exactly once, and that the variable-time impulsive systems can be reduced to the fixed-time impulsive ones. The obtained results imply that impulsive CGNN will remain stability property of continuous subsystem even if the impulses are of somewhat destabilizing, and that stabilizing impulses can stabilize the unstable continuous subsystem at its equilibrium points. Moreover, two stability criteria for the considered CGNN by use of proposed comparison system are obtained. Finally, the theoretical results are illustrated by two examples.

authors

• Huang, Tingwen

published proceedings

• INTERNATIONAL JOURNAL OF BIOMATHEMATICS

author list (cited authors)

• Zhang, X., Li, C., Huang, T., & Ahmad, H. G.

citation count

• 3

complete list of authors

• Zhang, Xianxiu||Li, Chuandong||Huang, Tingwen||Ahmad, Hafiz Gulfam

publication date

• November 2017

publisher

• World Scientific Publishing  Publisher

published in

• International Journal of Biomathematics  Journal

keywords

• B-equivalence
• Cohen?grossberg Neural Network (cgnn)
• Global Exponential Stability
• Variable-time Impulse

Digital Object Identifier (DOI)

• 10.1142/S1793524517501170

start page

• 1750117

end page

• 1750117

volume

• 10

issue

• 8

URL

• http://dx.doi.org/10.1142/s1793524517501170