Abstract
By combining the adaptive control and linear feedback with the updated laws, an approach of adaptive synchronization and parameters identification of recurrently delayed neural networks with all the parameters unknown is proposed based on the invariance principle of functional differential equations. This approach supplies a systematic and analytical procedure for adaptive synchronization and parameters identification of such uncertain networks, and it is also simple to implement in practice. Theoretical proof and numerical simulation demonstrate the effectiveness and feasibility of the proposed technique.
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Zhou, J., Chen, T., Xiang, L. (2005). Adaptive Synchronization of Delayed Neural Networks Based on Parameters Identification. In: Wang, J., Liao, X., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3496. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427391_48
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DOI: https://doi.org/10.1007/11427391_48
Publisher Name: Springer, Berlin, Heidelberg
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