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Neural Computing and Applications

Erschienen in:

01.10.2015 | Original Article

Exponential stability of inertial BAM neural networks with time-varying delay via periodically intermittent control

verfasst von: Wei Zhang, Chuandong Li, Tingwen Huang, Jie Tan

Erschienen in: Neural Computing and Applications | Ausgabe 7/2015

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Abstract

In this paper, we study global exponential stability problem for inertial BAM neural networks with time-varying delay via periodically intermittent control. By utilizing suitable variable substitution, the second-order system can be transformed into first-order differential equations. It is shown that the states of the inertial BAM neural networks with time-varying delay via periodically intermittent control can be globally exponential stabilized with a desired oribis under the designed intermittent controller. Finally, a typical example is chosen to illustrate the validation of the theoretical results.

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Titel: Exponential stability of inertial BAM neural networks with time-varying delay via periodically intermittent control
verfasst von: Wei Zhang
Chuandong Li
Tingwen Huang
Jie Tan
Publikationsdatum: 01.10.2015
Verlag: Springer London
Erschienen in: Neural Computing and Applications / Ausgabe 7/2015
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-015-1838-7

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