New Results on Finite/Fixed-Time Stabilization of Stochastic Second-Order Neutral-Type Neural Networks with Mixed Delays

被引：6
作者：
Aouiti, Chaouki [1 ]
Jallouli, Hediene [1 ]
Zhu, Quanxin [2 ]
Huang, Tingwen [3 ]
Shi, Kaibo [4 ]
机构：
[1] Univ Carthage, Fac Sci Bizerta, GAMA Lab LR21ES10, Dept Math, BP W, Zarzouna 7021, Bizerta, Tunisia
[2] Hunan Normal Univ, Sch Math & Stat, CHP LCOCS, Changsha 410081, Hunan, Peoples R China
[3] Texas A&M Univ Qatar, Sci Program, Doha 23874, Qatar
[4] Chengdu Univ, Sch Elect Informat & Elect Engn, Chengdu 610106, Peoples R China
来源：
NEURAL PROCESSING LETTERS | 2022年 / 54卷 / 06期
基金：
中国国家自然科学基金;
关键词：
Fixed-time stability; Finite-time stability; Inertial; Stochastic perturbations; Time-varying delays; EXPONENTIAL STABILITY; PROPORTIONAL DELAYS; FRACTIONAL-ORDER; STATE ESTIMATION; VARYING DELAY; SYNCHRONIZATION; SYSTEMS; DISCRETE; THEOREM;
D O I：
10.1007/s11063-022-10868-9
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper states with the objective of investigating the finite-time stabilization and fixed-time stabilization analysis for stochastic second-order neutral-type neural networks with mixed delays. By using a variable transformation, we first rewrite the original system as a first-order differential system. By designing some feedback control laws inputs, stochastic analysis theory, finite-time stability theorem, fixed-time stability theorem, based on Lyapunov Functionals and inequalities techniques, new sufficient conditions ensuring the finite/fixed-time stabilization of the suggested system are given. Finally, the developed main control schemes, the finite/fixed-time stabilization for the stochastic Neural Networks are confirmed by two simulations examples.
引用
收藏
页码：5415 / 5437
页数：23
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