A New Fixed-Time Stability Criterion and Its Application to Synchronization Control of Memristor-Based Fuzzy Inertial Neural Networks with Proportional Delay

被引：0
作者：
Yadan Zhang
Minghui Jiang
Xue Fang
机构：
[1] China Three Gorges University,Three Gorges Mathematical Research Center
[2] China Three Gorges University,Institute of Nonlinear Complex Systems
来源：
Neural Processing Letters | 2020年 / 52卷
关键词：
Fixed-time stability; Inertial neural networks; Memristor-based; Fuzzy;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper, a new criterion related to fixed-time stability is derived by strict mathematical techniques such as definite integral and inequality techniques. Compared with the existing theorems, the estimate of upper bound for settling time is smaller, which is not only proved theoretically but also shown by numerical simulations. And the new criterion gets improved after introducing a new lemma. Then on the basis of the new criterion and the improved theorem, the fixed-time synchronization (FTS) of a memristor-based fuzzy inertial neural network (MFINN) with proportional delay is investigated via adopting a delay-dependent feedback controller, and several sufficient conditions are given for the FTS of the MFINN. At last, numerical simulations are raised to substaintiate the correctness of our theoretical results.
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页码：1291 / 1315
页数：24
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