Output Synchronization in Coupled Neural Networks With and Without External Disturbances Academic Article

abstract

• © 2017 IEEE. 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.

authors

• Huang, Tingwen

published proceedings

• IEEE Transactions on Control of Network Systems

author list (cited authors)

• Wang, J., Wu, H., Huang, T., & Xu, M

citation count

• 41

complete list of authors

• Wang, Jin-Liang||Wu, Huai-Ning||Huang, Tingwen||Xu, Meng

publication date

• December 2018

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• IEEE Transactions on Control of Network Systems  Journal

keywords

• Coupled Neural Networks (cnns)
• Coupling Weights
• H-infinity Output Synchronization
• Output Synchronization

Digital Object Identifier (DOI)

• 10.1109/tcns.2017.2782488

start page

• 2049

end page

• 2061

volume

• 5

issue

• 4