Abstract
In this paper, the topic of fractional order digital differentiators (FODD) is designed using neural networks approximation method. First, FODD amplitude response is given in the form of sum of exponential basis functions. Then, the exponential basis function neural network is used to approximate FODD amplitude response. Finally, some examples compared with others’ method are given to illustrate the advantages of this paper approach.
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© 2006 Springer-Verlag Berlin Heidelberg
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Liao, K., Yuan, X., Pu, YF., Zhou, JL. (2006). Fractional Order Digital Differentiators Design Using Exponential Basis Function Neural Network. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3972. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760023_108
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DOI: https://doi.org/10.1007/11760023_108
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34437-7
Online ISBN: 978-3-540-34438-4
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