Abstract
This paper presents the adaptive synchronization between two different chaotic neural networks with fully unknown parameters and with time-delay. Based on the Lyapunov stability theory, the delay-dependent adaptive synchronization controller is designed to asymptotically synchronizing two different chaotic neural networks. A parameter update law is also given. The designed controller can easily be implemented in practice. An illustrative example is given to demonstrate the effectiveness of the present method.
This work is supported by a grant from National Laboratory of Space Intelligent Control and Open Foundation (No.SIC07010202) and the National Natural Science Foundation of China (No. 60604010, No. 90716021, No. 60736023).
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© 2009 Springer-Verlag Berlin Heidelberg
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Xie, Y., Sun, Z., Wang, F. (2009). Synchronization between Two Different Chaotic Neural Networks with Fully Unknown Parameters. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5552. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01510-6_135
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DOI: https://doi.org/10.1007/978-3-642-01510-6_135
Publisher Name: Springer, Berlin, Heidelberg
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