Output Synchronization in Coupled Neural Networks with and Without External Disturbances

Jin Liang Wang; Huai Ning Wu; Tingwen Huang; Meng Xu

doi:10.1109/TCNS.2017.2782488

Output Synchronization in Coupled Neural Networks with and Without External Disturbances

Jin Liang Wang
, Huai Ning Wu
, Tingwen Huang^*
, Meng Xu

^*Corresponding author for this work

School of Automation Science and Electrical Engineering

Tiangong University
Texas A&M University at Qatar

Research output: Contribution to journal › Article › peer-review

81 Scopus citations

Abstract

This paper studies the output synchronization of coupled neural networks (CNNs) as well as the effects of external disturbances. By employing matrix theory and Barbalat's Lemma, several output synchronization criteria are presented for CNNs with directed and undirected topologies, respectively. Moreover, in order to ensure the output synchronization of CNNs, two adaptive schemes to adjust the coupling weights are designed. On the other hand, we, respectively, analyze the H_∞ output synchronization of directed and undirected CNNs with external disturbances, and two adaptive strategies for updating the coupling weights are designed to guarantee the H_∞ output synchronization of CNNs. Finally, two examples of CNNs are also given to verify the proposed output synchronization criteria.

Original language	English
Article number	8186197
Pages (from-to)	2049-2061
Number of pages	13
Journal	IEEE Transactions on Control of Network Systems
Volume	5
Issue number	4
DOIs	https://doi.org/10.1109/TCNS.2017.2782488
State	Published - Dec 2018

Keywords

H output synchronization
coupled neural networks (CNNs)
coupling weights
output synchronization

Access to Document

10.1109/TCNS.2017.2782488

Cite this

@article{c0ec9824f3a44fb5ba7258068f8b09c5,

title = "Output Synchronization in Coupled Neural Networks with and Without External Disturbances",

abstract = "This paper studies the output synchronization of coupled neural networks (CNNs) as well as the effects of external disturbances. By employing matrix theory and Barbalat's Lemma, several output synchronization criteria are presented for CNNs with directed and undirected topologies, respectively. Moreover, in order to ensure the output synchronization of CNNs, two adaptive schemes to adjust the coupling weights are designed. On the other hand, we, respectively, analyze the H∞ output synchronization of directed and undirected CNNs with external disturbances, and two adaptive strategies for updating the coupling weights are designed to guarantee the H∞ output synchronization of CNNs. Finally, two examples of CNNs are also given to verify the proposed output synchronization criteria.",

keywords = "H output synchronization, coupled neural networks (CNNs), coupling weights, output synchronization",

author = "Wang, \{Jin Liang\} and Wu, \{Huai Ning\} and Tingwen Huang and Meng Xu",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.",

year = "2018",

month = dec,

doi = "10.1109/TCNS.2017.2782488",

language = "英语",

volume = "5",

pages = "2049--2061",

journal = "IEEE Transactions on Control of Network Systems",

issn = "2325-5870",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

number = "4",

}

TY - JOUR

T1 - Output Synchronization in Coupled Neural Networks with and Without External Disturbances

AU - Wang, Jin Liang

AU - Wu, Huai Ning

AU - Huang, Tingwen

AU - Xu, Meng

PY - 2018/12

Y1 - 2018/12

N2 - This paper studies the output synchronization of coupled neural networks (CNNs) as well as the effects of external disturbances. By employing matrix theory and Barbalat's Lemma, several output synchronization criteria are presented for CNNs with directed and undirected topologies, respectively. Moreover, in order to ensure the output synchronization of CNNs, two adaptive schemes to adjust the coupling weights are designed. On the other hand, we, respectively, analyze the H∞ output synchronization of directed and undirected CNNs with external disturbances, and two adaptive strategies for updating the coupling weights are designed to guarantee the H∞ output synchronization of CNNs. Finally, two examples of CNNs are also given to verify the proposed output synchronization criteria.

AB - This paper studies the output synchronization of coupled neural networks (CNNs) as well as the effects of external disturbances. By employing matrix theory and Barbalat's Lemma, several output synchronization criteria are presented for CNNs with directed and undirected topologies, respectively. Moreover, in order to ensure the output synchronization of CNNs, two adaptive schemes to adjust the coupling weights are designed. On the other hand, we, respectively, analyze the H∞ output synchronization of directed and undirected CNNs with external disturbances, and two adaptive strategies for updating the coupling weights are designed to guarantee the H∞ output synchronization of CNNs. Finally, two examples of CNNs are also given to verify the proposed output synchronization criteria.

KW - H output synchronization

KW - coupled neural networks (CNNs)

KW - coupling weights

KW - output synchronization

UR - https://www.scopus.com/pages/publications/85038367034

U2 - 10.1109/TCNS.2017.2782488

DO - 10.1109/TCNS.2017.2782488

M3 - 文章

AN - SCOPUS:85038367034

SN - 2325-5870

VL - 5

SP - 2049

EP - 2061

JO - IEEE Transactions on Control of Network Systems

JF - IEEE Transactions on Control of Network Systems

IS - 4

M1 - 8186197

ER -

Output Synchronization in Coupled Neural Networks with and Without External Disturbances

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this