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Identification of systems using radial basis networks feedbacked with FIR filters

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Computational Intelligence Theory and Applications (Fuzzy Days 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1226))

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Abstract

A new model of a radial basis neural network is presented in this article which is fedbacked with a FIR filter. Using various neurons of this type, it is possible to construct a recurrent neural network, where the coefficients of each filter and the synaptic connections are adjusted to minimize an error function. The simulations carried out show the validity of this method for identifying systems with memory.

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References

  1. A.G. Barto: Connectionist Learning for Control: An Overview. COINS Technical Report 89-89 (1989)

    Google Scholar 

  2. K.S. Narendra, K. Parthasarathy: Identification and control of dynamic systems using neural networks. IEEE Transactions on Neural Networks, Vol. 1, N∘ 1, 4–27 (1991)

    Google Scholar 

  3. E. S. Chng, S. Chen and B. Mulgrew: Improving the Radial Basis Function Networks for Homogeneous Nonstationary Time Series Prediction. European Signal Processing Conference VII 94 Edinburgh, 1819–1822 (1994)

    Google Scholar 

  4. I. B. Ciocoiu: Radial Basis Function Networks with FIR/IIR Synapses. Neural processing Letters 3, 17–22 (1996)

    Google Scholar 

  5. P.S. Sastry, G. Santharam, K.P. Unnikrishnan: Memory Neuron Networks for Identification and Control of Dynamical systems. IEEE Transactions on Neural Networks, Vol. 5, N∘ 2 (1994)

    Google Scholar 

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Authors and Affiliations

  1. Departamento de Electrónica, Universidad de Alcalá, 28801, Spain

    Luciano Boquete, Rafael Barea, Ricardo García, Manuel Mazo & J. A. Bernad

Authors
  1. Luciano Boquete
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  2. Rafael Barea
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  3. Ricardo García
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  4. Manuel Mazo
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  5. J. A. Bernad
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Editor information

Bernd Reusch

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© 1997 Springer-Verlag Berlin Heidelberg

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Boquete, L., Barea, R., García, R., Mazo, M., Bernad, J.A. (1997). Identification of systems using radial basis networks feedbacked with FIR filters. In: Reusch, B. (eds) Computational Intelligence Theory and Applications. Fuzzy Days 1997. Lecture Notes in Computer Science, vol 1226. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-62868-1_96

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  • DOI: https://doi.org/10.1007/3-540-62868-1_96

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-62868-2

  • Online ISBN: 978-3-540-69031-3

  • eBook Packages: Springer Book Archive

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