Exponential Stability and Periodicity of Fuzzy Delayed Reaction-Diffusion Cellular Neural Networks with Impulsive Effect
This paper considers dynamical behaviors of a class of fuzzy impulsive reaction-diffusion delayed cellular neural networks (FIRDDCNNs) with time-varying periodic self-inhibitions, interconnection weights, and inputs. By using delay differential inequality, M-matrix theory, and analytic methods, some...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2013-01-01
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| Series: | Abstract and Applied Analysis |
| Online Access: | http://dx.doi.org/10.1155/2013/645262 |
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| Summary: | This paper considers dynamical behaviors of a class of fuzzy
impulsive reaction-diffusion delayed cellular neural networks
(FIRDDCNNs) with time-varying periodic self-inhibitions,
interconnection weights, and inputs. By using delay differential
inequality, M-matrix theory, and analytic methods, some new
sufficient conditions ensuring global exponential stability of the
periodic FIRDDCNN model with Neumann boundary conditions are
established, and the exponential convergence rate index is
estimated. The differentiability of the time-varying delays is not
needed. An example is presented to demonstrate the efficiency and
effectiveness of the obtained results. |
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| ISSN: | 1085-3375 1687-0409 |