General decay stability analysis of coupled systems of stochastic neural networks
Date Issued
2019
Author(s)
Abstract
This paper covers the topic of the pth moment (p ≥ 2) stability of coupled systems of stochastic Cohen-Grossberg neural networks with time delays, impulses and Markovian switching. This model generalises many models in the literature and to the best of our knowledge has
not been analyzed before. The methods are based on results from graph theory, Lyapunov operator, Dini derivative and some known inequality techniques. Additionally, we consider the stability with respect to a general decay function which includes exponential, but also more general lower rate decay functions as the polynomial and the logarithmic ones.
This fact gives us the opportunity to study general decay stability, even when the exponential one cannot be discussed. The presented theoretical results are supported by a numerical example.
not been analyzed before. The methods are based on results from graph theory, Lyapunov operator, Dini derivative and some known inequality techniques. Additionally, we consider the stability with respect to a general decay function which includes exponential, but also more general lower rate decay functions as the polynomial and the logarithmic ones.
This fact gives us the opportunity to study general decay stability, even when the exponential one cannot be discussed. The presented theoretical results are supported by a numerical example.
Subjects