Impulsive Effects and Stability Analysis on Memristive Neural Networks With Variable Delays. Academic Article

abstract

• In this brief, hybrid impulsive and adaptive feedback controllers are simultaneously exerted on a general delayed memristive neural network (MNN) model to formulate a novel impulsive controlled MNN (IMNN) model with variable delays. By means of Lyapunov-Razumikhin technique and other analytical ways, several new stability criteria of the proposed IMNN model are obtained. In addition, by choosing appropriate impulses and external inputs, the convergence speed of IMNN can be increased, which implies that its dynamic behaviors will be optimized. Finally, the effectiveness of the obtained results is illustrated by one numerical example.

authors

• Huang, Tingwen

published proceedings

• IEEE Trans Neural Netw Learn Syst

author list (cited authors)

• Duan, S., Wang, H., Wang, L., Huang, T., & Li, C.

citation count

• 50

complete list of authors

• Duan, Shukai||Wang, Huamin||Wang, Lidan||Huang, Tingwen||Li, Chuandong

publication date

• February 2017

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• n2162-237XISSN  Journal

keywords

• Exponential Stability
• Impulsive Effects
• Memristive Neural Networks (mnns)
• Optimization

Digital Object Identifier (DOI)

• 10.1109/TNNLS.2015.2497319

start page

• 476

end page

• 481

volume

• 28

issue

• 2

URL

• http://dx.doi.org/10.1109/tnnls.2015.2497319