Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4629571 | Applied Mathematics and Computation | 2012 | 14 Pages |
Abstract
To the best of our knowledge, there are only few results on general decay stability applied to stochastic neural networks. For stochastic Cohen–Grossberg neural networks with time-varying delays, we study in the present paper both the p th moment (p⩾2)(p⩾2) and almost sure stability on a general decay rate and partly generalize and improve some known results referring to the exponential stability. We also extend the usual notion on a general decay function, which allows us to study both the pth moment and almost sure stability even if the exponential stability cannot be shown. Some examples are presented to support and illustrate the theory.
Keywords
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Biljana Tojtovska, Svetlana Janković,