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Zbl 1185.35129
Song, Qiankun; Wang, Zidong
Dynamical behaviors of fuzzy reaction-diffusion periodic cellular neural networks with variable coefficients and delays. (English)
[J] Appl. Math. Modelling 33, No. 9, 3533-3545 (2009). ISSN 0307-904X

Summary: When modeling neural networks in a real world, not only diffusion effect and fuzziness cannot be avoided, but also self-inhibitions, interconnection weights, and inputs should vary as time varies. In this paper, we discuss the dynamical behaviors of delayed reaction-diffusion fuzzy cellular neural networks with varying periodic self-inhibitions, interconnection weights as well as inputs. By using Halanay's delay differential inequality, $M$-matrix theory and analytic methods, some new sufficient conditions are obtained to ensure the existence, uniqueness, and global exponential stability of the periodic solution, and the exponentially convergent rate index is also estimated. In particular, the traditional assumption on the differentiability of the time-varying delays is no longer needed. The methodology developed in this paper is shown to be simple and effective for the exponential periodicity and stability analysis of neural networks with time-varying delays. Two examples are given to show the usefulness of the obtained results that are less restrictive than recently known criteria.

MSC 2000:: *35K57 Reaction-diffusion equations
37N25 Dynamical systems in biology
92B20 General theory of neural networks

Keywords: fuzzy cellular neural networks; reaction-diffusion; time-varying delays; periodic solutions; stability; exponential convergence

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