Synchronization of Memristor-Based Coupling Recurrent Neural Networks With Time-Varying Delays and Impulses. Academic Article

abstract

• Synchronization of an array of linearly coupled memristor-based recurrent neural networks with impulses and time-varying delays is investigated in this brief. Based on the Lyapunov function method, an extended Halanay differential inequality and a new delay impulsive differential inequality, some sufficient conditions are derived, which depend on impulsive and coupling delays to guarantee the exponential synchronization of the memristor-based recurrent neural networks. Impulses with and without delay and time-varying delay are considered for modeling the coupled neural networks simultaneously, which renders more practical significance of our current research. Finally, numerical simulations are given to verify the effectiveness of the theoretical results.

authors

• Huang, Tingwen

published proceedings

• IEEE Trans Neural Netw Learn Syst

author list (cited authors)

• Zhang, W., Li, C., Huang, T., & He, X.

citation count

• 111

complete list of authors

• Zhang, Wei||Li, Chuandong||Huang, Tingwen||He, Xing

publication date

• December 2015

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• n2162-237XISSN  Journal

keywords

• Algorithms
• Computer Simulation
• Feedback
• Neural Networks, Computer
• Nonlinear Dynamics
• Time Factors

Digital Object Identifier (DOI)

• 10.1109/TNNLS.2015.2435794

start page

• 3308

end page

• 3313

volume

• 26

issue

• 12

URL

• http://dx.doi.org/10.1109/tnnls.2015.2435794