Passivity and synchronization of coupled complex-valued memristive neural networks

Yanli Huang; Jie Hou; Shunyan Ren; Erfu Yang

doi:10.1109/SSCI44817.2019.9002792

Passivity and synchronization of coupled complex-valued memristive neural networks

Yanli Huang, Jie Hou, Shunyan Ren, Erfu Yang

Design, Manufacturing And Engineering Management

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

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Abstract

The coupled complex-valued memristive neural networks (CCVMNNs) are investigated in this study. First, we analyze the passivity of the proposed network model by designing an appropriate controller and using certain inequalities as well as Lyapunov functional method, and provide a passivity condition for the considered CCVMNNs. In addition, a criterion for guaranteeing synchronization of this kind of network is established. Finally, the effectiveness and correctness of the acquired theoretical results are verified by a numerical example.

Original language	English
Title of host publication	2019 IEEE Symposium Series on Computational Intelligence
Place of Publication	Piscataway, NJ
Publisher	IEEE
Pages	2152-2159
Number of pages	8
ISBN (Electronic)	9781728124858
ISBN (Print)	9781728124858
DOIs	https://doi.org/10.1109/SSCI44817.2019.9002792
Publication status	Published - 20 Feb 2020
Event	2019 IEEE Symposium Series on Computational Intelligence, SSCI 2019 - Xiamen, China Duration: 6 Dec 2019 → 9 Dec 2019

Conference

Conference	2019 IEEE Symposium Series on Computational Intelligence, SSCI 2019
Country/Territory	China
City	Xiamen
Period	6/12/19 → 9/12/19

Keywords

memristive neural networks
passivity
state coupling
synchronization

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10.1109/SSCI44817.2019.9002792

Huang-etal-SSCI2019-Passivity-and-synchronization-of-coupled-complex-valuedAccepted author manuscript, 762 KB

Cite this

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abstract = "The coupled complex-valued memristive neural networks (CCVMNNs) are investigated in this study. First, we analyze the passivity of the proposed network model by designing an appropriate controller and using certain inequalities as well as Lyapunov functional method, and provide a passivity condition for the considered CCVMNNs. In addition, a criterion for guaranteeing synchronization of this kind of network is established. Finally, the effectiveness and correctness of the acquired theoretical results are verified by a numerical example.",

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Huang, Y, Hou, J, Ren, S & Yang, E 2020, Passivity and synchronization of coupled complex-valued memristive neural networks. in 2019 IEEE Symposium Series on Computational Intelligence., 9002792, IEEE, Piscataway, NJ, pp. 2152-2159, 2019 IEEE Symposium Series on Computational Intelligence, SSCI 2019, Xiamen, China, 6/12/19. https://doi.org/10.1109/SSCI44817.2019.9002792

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AU - Huang, Yanli

AU - Hou, Jie

AU - Ren, Shunyan

AU - Yang, Erfu

N1 - © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

PY - 2020/2/20

Y1 - 2020/2/20

N2 - The coupled complex-valued memristive neural networks (CCVMNNs) are investigated in this study. First, we analyze the passivity of the proposed network model by designing an appropriate controller and using certain inequalities as well as Lyapunov functional method, and provide a passivity condition for the considered CCVMNNs. In addition, a criterion for guaranteeing synchronization of this kind of network is established. Finally, the effectiveness and correctness of the acquired theoretical results are verified by a numerical example.

AB - The coupled complex-valued memristive neural networks (CCVMNNs) are investigated in this study. First, we analyze the passivity of the proposed network model by designing an appropriate controller and using certain inequalities as well as Lyapunov functional method, and provide a passivity condition for the considered CCVMNNs. In addition, a criterion for guaranteeing synchronization of this kind of network is established. Finally, the effectiveness and correctness of the acquired theoretical results are verified by a numerical example.

KW - memristive neural networks

KW - passivity

KW - state coupling

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BT - 2019 IEEE Symposium Series on Computational Intelligence

PB - IEEE

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T2 - 2019 IEEE Symposium Series on Computational Intelligence, SSCI 2019

Y2 - 6 December 2019 through 9 December 2019

ER -

Passivity and synchronization of coupled complex-valued memristive neural networks

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