Abstract
Recently, an approach for rapid dynamical pattern recognition was proposed, by which a dynamical pattern can be locally accurately identified and rapidly recognized using localized radial basis function (RBF) networks. Further, a scheme for classification of dynamical patterns was presented. In this paper, we investigate the construction of the recognition system for classification of Lorenz system and Chen system, both of which can generate various types of dynamical patterns. Simulation studies are included to demonstrate the effectiveness of this method.
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Cheng, H., Wang, C. (2008). Dynamical Pattern Classification of Lorenz System and Chen System. In: Sun, F., Zhang, J., Tan, Y., Cao, J., Yu, W. (eds) Advances in Neural Networks - ISNN 2008. ISNN 2008. Lecture Notes in Computer Science, vol 5264. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87734-9_37
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DOI: https://doi.org/10.1007/978-3-540-87734-9_37
Publisher Name: Springer, Berlin, Heidelberg
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