Paper Info
Title
Exponential P-Stability Of Stochastic Reaction-Diffusion Cellular Neural Networks With Multiple Delays
Abstract
In the current paper, a class of stochastic cellular neural networks with reaction-diffusion effects, both discrete and distributed time delays, is studied. Several sufficient conditions guaranteeing the almost sure and pth moment exponential stability of its equilibrium solution are respectively obtained through analytic methods such as employing Lyapunov functional, applying Ito's formula, inequality techniques, embedding in Banach space, Matrix analysis and semimartingale convergence theorem. The yielded conclusions, which are independent of diffusion terms and delays, assume much less restrictions on activation functions and interconnection weights, and can be applied within a broader range of neural networks. Moreover, through the obtained results, it could be noted that noise will affect the exponential stability of the system. For illustration, two examples are given to show the feasibility of results.
Year
DOI
Venue
2009
10.1142/S0218127409024815
INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS
Keywords
DocType
Volume
Stochastic neural networks, pth moment exponential stability, reaction-diffusion, time-delay, semimartingale, Lyapunov functional
Journal
19
Issue
ISSN
Citations 
10
0218-1274
1
PageRank 
References 
Authors
0.40
9
1
Name
Order
Citations
PageRank
Ranchao Wu118910.45