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Complex Process Visualization through Continuous Feature Maps Using Radial Basis Functions

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Artificial Neural Networks — ICANN 2001 (ICANN 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2130))

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Abstract

In this paper we propose a method for complex process visualization using a continuous mapping from the space of measurements or features of the process onto a continuous visualization space. To construct this mapping we suggest a continuous extension of the self organizing map using a kernel regression approach. We also describe a method for continuous condition monitoring based on the proposed continous mapping. We finally illustrate the proposed method with experimental data from an induction motor working in different fault conditions.

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© 2001 Springer-Verlag Berlin Heidelberg

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Díaz, I., Diez, A., Vega, A.A.C. (2001). Complex Process Visualization through Continuous Feature Maps Using Radial Basis Functions. In: Dorffner, G., Bischof, H., Hornik, K. (eds) Artificial Neural Networks — ICANN 2001. ICANN 2001. Lecture Notes in Computer Science, vol 2130. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44668-0_62

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  • DOI: https://doi.org/10.1007/3-540-44668-0_62

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42486-4

  • Online ISBN: 978-3-540-44668-2

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