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International Symposium on Computer and Information Sciences

ISCIS 2003: Computer and Information Sciences - ISCIS 2003 pp 601–610Cite as

Nonlinear Filtering Design Using Dynamic Neural Networks with Fast Training

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2869))

Abstract

This paper presents nonlinear filtering using dynamic neural networks (DNNs). In addition, the general usage of linear filtering structure is given. DNN which has a quasi-linear structure has been effectively used as a filter with fast training algorithm such as Levenberg-Marquardt method. The test results are shown that the performance of DNN as linear and nonlinear filters is satisfactory.

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Author information

Authors and Affiliations

  1. Computer Engineering Depart, Kocaeli University, Izmit, Turkey

    Yasar Becerikli

Authors
  1. Yasar Becerikli
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Editor information

Editors and Affiliations

  1. Dept. of Computer Engineering, Middle East Technical University, Ankara, Turkey

    Adnan Yazıcı

  2. Department of Computer Engineering, Middle East Technical University, 06531, Ankara, Turkey

    Cevat Şener

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Becerikli, Y. (2003). Nonlinear Filtering Design Using Dynamic Neural Networks with Fast Training. In: Yazıcı, A., Şener, C. (eds) Computer and Information Sciences - ISCIS 2003. ISCIS 2003. Lecture Notes in Computer Science, vol 2869. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39737-3_75

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  • DOI: https://doi.org/10.1007/978-3-540-39737-3_75

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-20409-1

  • Online ISBN: 978-3-540-39737-3

  • eBook Packages: Springer Book Archive

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