Dynamic behaviors of memristor-based delayed recurrent networks Academic Article

abstract

• This paper investigates the problem of the existence and global exponential stability of the periodic solution of memristor-based delayed network. Based on the knowledge of memristor and recurrent neural network, the model of the memristor-based recurrent networks is established. Several sufficient conditions are obtained, which ensure the existence of periodic solutions and global exponential stability of the memristor-based delayed recurrent networks. These results ensure global exponential stability of memristor-based network in the sense of Filippov solutions. And, it is convenient to estimate the exponential convergence rates of this network by the results. An illustrative example is given to show the effectiveness of the theoretical results. 2012 Springer-Verlag London Limited.

authors

• Huang, Tingwen

published proceedings

• NEURAL COMPUTING & APPLICATIONS

author list (cited authors)

• Wen, S., Zeng, Z., & Huang, T.

citation count

• 59

complete list of authors

• Wen, Shiping||Zeng, Zhigang||Huang, Tingwen

publication date

• September 2013

publisher

• Springer Nature  Publisher

published in

• Neural Computing and Applications  Journal

keywords

• Memristor
• Recurrent Networks
• Time Delays

Digital Object Identifier (DOI)

• 10.1007/s00521-012-0998-y

start page

• 815

end page

• 821

volume

• 23

issue

• 3-4

URL

• http://dx.doi.org/10.1007/s00521-012-0998-y