Stability of inertial SAM neural network with time-varying delay via impulsive control Academic Article

abstract

• 2015 Elsevier B.V. In this paper, a class of inertial BAM neural networks with time-varying delays is considered. By choosing proper variable transformation, the inertial BAM neural networks can be rewritten as first-order differential equations. Based on the Lyapunov functional method and the comparison principle, we derive some sufficient conditions guaranteeing the exponential stability of the neural networks under impulsive control. For different equilibrium point, the different impulsive controller can be obtained. Moreover, less conservatism impulsive controller will be designed to stabilize the zero equilibrium point. Simulation results finally demonstrate the effectiveness of the theoretical results.

authors

• Huang, Tingwen

published proceedings

• NEUROCOMPUTING

author list (cited authors)

• Qi, J., Li, C., & Huang, T.

citation count

• 89

complete list of authors

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

publication date

• August 2015

publisher

• Elsevier  Publisher

published in

• Neurocomputing  Journal

keywords

• Global Exponential
• Impulsive Effects
• Inertial Bam Neural Network
• Time-varying Delays

Digital Object Identifier (DOI)

• 10.1016/j.neucom.2015.02.052

start page

• 162

end page

• 167

volume

• 161

URL

• http%3A%2F%2Fdx.doi.org%2F10.1016%2Fj.neucom.2015.02.052