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Kernel CMAC with Reduced Memory Complexity

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Artificial Neural Networks – ICANN 2009 (ICANN 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5768))

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Abstract

Cerebellar Model Articulation Controller (CMAC) has some attractive features: fast learning capability and the possibility of efficient digital hardware implementation. Besides these attractive features it has a serious drawback: its memory complexity may be very large. In multidimensional case this may be so large that practically it cannot be implemented. To reduce memory complexity several different approaches were suggested so far. Although these approaches may greatly reduce memory complexity we have to pay a price for this complexity reduction. Either both modelling and generalization capabilities are deteriorated, or the training process will be much more complicated. This paper proposes a new approach of complexity reduction, where properly constructed hash-coding is combined with regularized kernel representation. The proposed version exploits the benefits of kernel representation and the complexity reduction effect of hash-coding, while smoothing regularization helps to reduce the performance degradation.

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Authors and Affiliations

  1. Department of Measurement and Information Systems, Budapest University of Technology and Economics, Magyar tudósok krt. 2., Budapest, Hungary, H-1117

    Gábor Horváth & Kristóf Gáti

Authors
  1. Gábor Horváth
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  2. Kristóf Gáti
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Editor information

Editors and Affiliations

  1. Dipartimento di Elettronica, Politecnico di Milano, Piazza L. da Vinci 32, 20133, Milano, Italy

    Cesare Alippi

  2. Department of Electrical and Computer Engineering, University of Cyprus, 75 Kallipoleos Street, 1678, Nicosia, Cyprus

    Marios Polycarpou , Christos Panayiotou  & Georgios Ellinas ,  & 

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Horváth, G., Gáti, K. (2009). Kernel CMAC with Reduced Memory Complexity. In: Alippi, C., Polycarpou, M., Panayiotou, C., Ellinas, G. (eds) Artificial Neural Networks – ICANN 2009. ICANN 2009. Lecture Notes in Computer Science, vol 5768. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04274-4_72

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  • DOI: https://doi.org/10.1007/978-3-642-04274-4_72

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04273-7

  • Online ISBN: 978-3-642-04274-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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