Novel Stability Criteria for Impulsive Memristive Neural Networks with Time-Varying Delays Academic Article

abstract

• 2016, Springer Science+Business Media New York. In order to improve the ability of resisting disturbance for memristive neural networks (MNNs), a general impulsive controlled MNN with variable delays is constructed in this paper. Then, its dynamical behaviors are investigated based on the differential inclusion theories. By constructing suitable LyapunovKrasovskii-type functional and combining with integral and monotone function method, the global exponential stability criteria of delayed memristive neural networks (DMNNs) with impulse effects are derived. Furthermore, the impulsive controlled DMNNs can be transformed to DMNNs without impulsive effects, which promote and enrich the theoretical research results of MNNs. Finally, the effectiveness of obtained results is illustrated by two numerical examples.

authors

• Huang, Tingwen

published proceedings

• CIRCUITS SYSTEMS AND SIGNAL PROCESSING

author list (cited authors)

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

citation count

• 16

complete list of authors

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

publication date

• January 2016

publisher

• Springer Nature  Publisher

published in

• Circuits, Systems and Signal Processing  Journal

keywords

• Global Exponential Stability
• Impulse Effects
• Memristive Neural Networks
• Time-varying Delays

Digital Object Identifier (DOI)

• 10.1007/s00034-015-0240-0

start page

• 3935

end page

• 3956

volume

• 35

issue

• 11

URL

• http://dx.doi.org/10.1007/s00034-015-0240-0