Abstract
Based on Elman network, the recurrent wavelet neural network (RWNN) is presented, and the extended kalman filter of RWNN is given in this paper. The recurrent wavelet neural network (RWNN) can be used in the nonlinear system identification successfully. Practical example shows that RWNN has a faster convergence as well as a better precision in calculation, and a good result on the nonlinear system identification is got, which means it has a broad prospect on application.
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© 2009 Springer-Verlag Berlin Heidelberg
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Zhao, F., Hu, L., Li, Z. (2009). Nonlinear System Identification Based on Recurrent Wavelet Neural Network. In: Wang, H., Shen, Y., Huang, T., Zeng, Z. (eds) The Sixth International Symposium on Neural Networks (ISNN 2009). Advances in Intelligent and Soft Computing, vol 56. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01216-7_54
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DOI: https://doi.org/10.1007/978-3-642-01216-7_54
Publisher Name: Springer, Berlin, Heidelberg
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