Stability of delayed memristive neural networks with time-varying impulses.

abstract

• This paper addresses the stability problem on the memristive neural networks with time-varying impulses. Based on the memristor theory and neural network theory, the model of the memristor-based neural network is established. Different from the most publications on memristive networks with fixed-time impulse effects, we consider the case of time-varying impulses. Both the destabilizing and stabilizing impulses exist in the model simultaneously. Through controlling the time intervals of the stabilizing and destabilizing impulses, we ensure the effect of the impulses is stabilizing. Several sufficient conditions for the globally exponentially stability of memristive neural networks with time-varying impulses are proposed. The simulation results demonstrate the effectiveness of the theoretical results.

authors

• Huang, Tingwen

published proceedings

• Cogn Neurodyn

author list (cited authors)

• Qi, J., Li, C., & Huang, T.

citation count

• 40

complete list of authors

• Qi, Jiangtao||Li, Chuandong||Huang, Tingwen

publication date

• October 2014

publisher

• Springer Nature  Publisher

published in

• Cognitive Neurodynamics  Journal

keywords

• Exponential Stability
• Memristive Neural Networks
• Time-varying Delays
• Time-varying Impulses

PubMed Central ID

• 25206936

Digital Object Identifier (DOI)

• 10.1007/s11571-014-9286-0

start page

• 429

end page

• 436

volume

• 8

issue

• 5

URL

• http://dx.doi.org/10.1007/s11571-014-9286-0