<inline-formula> <tex-math notation="LaTeX">$2p$ </tex-math></inline-formula>-th Moment Global Exponential Stability of a Unique <inline-formula> <tex-math notation="LaTeX">$2P$ </tex-math></inline-formula>-th Mean Almost Periodic Oscillation for Semi-Discrete Takagi-Sugeno Fuzzy Stochastic Cellular Neural Networks With Time Delays

Abstract

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.

Keywords

• Moment global exponential stability
• semi-discrete method
• stochastics
• Takagi-Sugeno approach