Global exponential synchronization of nonautonomous recurrent neural networks with time delays on time scales Academic Article

abstract

• 2018 Elsevier Inc. This paper is concerned on the global exponential synchronization in timescale sense for a class of nonautonomous recurrent neural networks (NRNNs) with discrete-time delays on time scales. Firstly, a timescale-type comparison result is given based on the induction principle of time scales. Then by the constructed comparison lemma, the theory of time scales and analytical techniques, several synchronization criteria for the driven and response NRNNs are obtained. Moreover, several examples are given to show the effectiveness and validity of the main results. The obtained synchronization criteria improve or extend some existing ones in the literature.

authors

• Huang, Tingwen

published proceedings

• APPLIED MATHEMATICS AND COMPUTATION

author list (cited authors)

• Wang, L., Huang, T., & Xiao, Q.

citation count

• 9

complete list of authors

• Wang, Lingyu||Huang, Tingwen||Xiao, Qiang

publication date

• July 2018

publisher

• Elsevier  Publisher

published in

• Applied Mathematics and Computation  Journal

keywords

• Global Exponential Synchronization
• Nonautonomous Recurrent Neural Networks
• Time Delay
• Time Scale

Digital Object Identifier (DOI)

• 10.1016/j.amc.2018.01.029

start page

• 263

end page

• 275

volume

• 328

URL

• http://dx.doi.org/10.1016/j.amc.2018.01.029