Robustness analysis of stability of Takagi-Sugeno type fuzzy neural network
Wenxiang Fang, Tao Xie · AIMS Mathematics · 2023
In this paper, inequality techniques, stochastic analysis and algebraic methods are used to analyze the robustness of the stability of recurrent neural networks containing Takagi-Sugeno fuzzy rules. By solving the transcendental equations, the upper bounds of time delay and noise intensity are given, and the dynamic relationship between the two disturbance factors is derived. Finally, numerical examples are given to verify the results of this paper.