Global exponential synchronization of inertial memristive neural networks with time-varying delay via nonlinear controller. Academic Article

abstract

• The paper is concerned with the synchronization problem of inertial memristive neural networks with time-varying delay. First, by choosing a proper variable substitution, inertial memristive neural networks described by second-order differential equations can be transformed into first-order differential equations. Then, a novel controller with a linear diffusive term and discontinuous sign term is designed. By using the controller, the sufficient conditions for assuring the global exponential synchronization of the derive and response neural networks are derived based on Lyapunov stability theory and some inequality techniques. Finally, several numerical simulations are provided to substantiate the effectiveness of the theoretical results.

authors

• Huang, Tingwen

published proceedings

• Neural Netw

author list (cited authors)

• Gong, S., Yang, S., Guo, Z., & Huang, T.

citation count

• 52

complete list of authors

• Gong, Shuqing||Yang, Shaofu||Guo, Zhenyuan||Huang, Tingwen

publication date

• June 2018

publisher

• Elsevier  Publisher

published in

• Neural Networks  Journal

keywords

• Inertial Memristive Neural Network
• Machine Learning
• Neural Networks, Computer
• Nonlinear Controller
• Nonlinear Dynamics
• Synchronization
• Time Factors
• Time-varying Delay

PubMed Central ID

• 29597184

Digital Object Identifier (DOI)

• 10.1016/j.neunet.2018.03.001

start page

• 138

end page

• 148

volume

• 102

URL

• http://dx.doi.org/10.1016/j.neunet.2018.03.001