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Reachable Set Estimation of Inertial Complex-Valued Memristive Neural Networks

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成果类型:
期刊论文
作者:
Zhao, Jiemei;Shen, Yi;Wang, Leimin;Yu, Liqi
通讯作者:
Zhao, JM
作者机构:
[Zhao, Jiemei; Shen, Yi] Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan 430023, Peoples R China.
[Wang, Leimin] China Univ Geosci, Sch Automat, Wuhan 430074, Peoples R China.
[Yu, Liqi] East Univ Heilongjiang, Math Dept, Harbin 150066, Peoples R China.
通讯机构:
[Zhao, JM ] W
Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan 430023, Peoples R China.
语种:
英文
关键词:
Neural networks;Ellipsoids;Estimation;Circuits;Synchronization;Switches;Neurons;Vectors;Postal services;Nonlinear dynamical systems;Memristive neural networks;reachable set;inertia term;complex-valued
期刊:
IEEE Transactions on Circuits and Systems II: Express Briefs
ISSN:
1549-7747
年:
2025
卷:
72
期:
1
页码:
213-217
基金类别:
10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 62473348) 10.13039/501100001809-Natural Science Foundation of Wuhan (Chenguang Project) (Grant Number: 2024040801020332) 10.13039/501100005046-Natural Science Foundation of Heilongjiang Province (Grant Number: LH2022A022)
机构署名:
本校为第一且通讯机构
院系归属:
数学与计算机学院
摘要:
This brief investigates the reachable set estimation (RSE) of inertial complex-valued memristive neural networks (ICVMNNs) with bounded disturbances. By taking into account the analysis method and inequality technique, an algebraic criterion of RES is established. To deal with the inertial terms in memristive neural networks, a nonreduced-order approach is adopted. Besides, the non-separation analysis method is applied to investigate complex-valued problems. Then, a complex-valued feedback control scheme is designed to ensure that the states of ICVMNNs converge to a bounded region. Eventually,...

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