Finite/fixed-time synchronization of delayed memristive reaction-diffusion neural networks Academic Article

abstract

• 2019 Elsevier B.V. This paper is concerned with the finite/fixed-time synchronization (FFTS) problems of two delayed memristive reactiondiffusion neural networks (MRDNNs). By designing appropriate state feedback controllers, utilizing the Lyapunov function method and inequality techniques, several sufficient criteria are derived to guarantee the FFTS of the drive-response MRDNNs. Taking into account both the influences of time and space, the model, described as a state-dependent switching system here, is more complex and closer to practical applications than those in the existing results. Finally, an example is presented to substantiate the effectiveness of the theoretical results.

authors

• Huang, Tingwen

published proceedings

• NEUROCOMPUTING

author list (cited authors)

• Wang, S., Guo, Z., Wen, S., Huang, T., & Gong, S.

citation count

• 26

complete list of authors

• Wang, Shiqin||Guo, Zhenyuan||Wen, Shiping||Huang, Tingwen||Gong, Shuqing

publication date

• January 2020

publisher

• Elsevier  Publisher

published in

• Neurocomputing  Journal

keywords

• Finite/fixed-time Synchronization
• Memristive Neural Network
• Reaction-diffusion
• State Feedback Controller

Digital Object Identifier (DOI)

• 10.1016/j.neucom.2019.06.092

start page

• 1

end page

• 8

volume

• 375

URL

• http://dx.doi.org/10.1016/j.neucom.2019.06.092