Exponential \({H_\infty }\) Filtering for Discrete-Time Switched Neural Networks with Mode-Dependent Average Dwell Time

会议论文
发表日期：

2026年

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Dan Li,
Jinling Wang,
Jiarong Li,
Qing-Hao Zhang,
Zhen Zhu,
Jun-Guo Lu

摘要

This paper studies the exponential \(H_\infty \) filtering problem for discrete-time switched neural networks (SNNs) under mode-dependent average dwell time (MDADT). First, we establish the global uniform exponential stability for the filtering error system. Second, we quantify noise attenuation through a weighted \(l_2\) -gain \(H_\infty \) performance index. Finally, numerical simulations demonstrate the validity of derived results.