IJPAM: Volume 96, No. 1 (2014)
NEURAL NETWORKS WITH MIXED TIME-VARYING
DELAYS VIA HYBRID INTERMITTENT
Department of Mathematics
Bangkok, 10110, THAILAND
Abstract. In this paper, we investigate the problem of exponential synchronization for master-slave neural networks with mixed time-varying delays via hybrid intermittent feedback control. The constraint on the derivative of the time-varying delay is not required which allows the time-delay to be a fast time-varying function. Based on the construction of improved Lyapunov-Krasovskii functionals is combined with Leibniz-Newton’s formula and the technique of dealing with some integral terms. New delay-dependent sufficient conditions for the exponential synchronization of the error systems with memoryless hybrid feedback control are first established in terms of LMIs without introducing any free-weighting matrices. The designed controller ensures that the synchronization of the error systems are proposed via hybrid intermittent feedback control. Numerical simulations are presented to illustrate the effectiveness of these synchronization criteria.
Received: May 15, 2014
AMS Subject Classification: 34D06, 92B20, 93B52
Key Words and Phrases: master-slave neural networks, exponential synchronization, mixed time-varying delays, intermittent feedback control
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DOI: 10.12732/ijpam.v96i1.6 How to cite this paper?
Source: International Journal of Pure and Applied Mathematics
ISSN printed version: 1311-8080
ISSN on-line version: 1314-3395
Pages: 59 - 78