2p -th Moment Global Exponential Stability of a Unique 2P -th Mean Almost Periodic Oscillation for Semi-Discrete Takagi-Sugeno Fuzzy Stochastic Cellular Neural Networks With Time Delays
By using semi-discrete and Takagi-Sugeno fuzzy methods, a new version of discrete analogue of stochastic fuzzy cellular neural networks is formulated, which gives a more accurate characterization for continuous-time stochastic model than that by Euler scheme. Firstly, the 2p -th moment global expon...
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Veröffentlicht in: | IEEE access 2019, Vol.7, p.114747-114760 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | By using semi-discrete and Takagi-Sugeno fuzzy methods, a new version of discrete analogue of stochastic fuzzy cellular neural networks is formulated, which gives a more accurate characterization for continuous-time stochastic model than that by Euler scheme. Firstly, the 2p -th moment global exponential stability for the obtained semi-discrete stochastic Takagi-Sugeno fuzzy model is studied with the help of Minkowski inequality and Hölder inequality. Secondly, the 2p -th mean almost periodic outputs of the model is investigated by using Krasnoselskii's fixed point theorem. Finally, illustrative examples and numerical simulations are given to demonstrate that our results are feasible. |
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ISSN: | 2169-3536 2169-3536 |
DOI: | 10.1109/ACCESS.2019.2935243 |