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The Continuous Interpolating Self-organizing Map

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Abstract

The self-organizing map (SOM) [5] provides a general data approximation method which is suitable for several application domains. The topology preservation is an important feature in data-analysis and may also be advantageous for the evaluation of the data in a function approximation or regression task. For this reason the interpolated self-organizing map (I-SOM) adds an output layer to the SOM architecture which computes a real valued output vector. This paper presents an extension of I-SOM towards a continuous interpolation. It is compared to RBF and to the parametrized self-organizing map.

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Authors and Affiliations

  1. University of Tübingen, Sand 13, D-72076, Tübingen, Germany

    J. Göppert & W. Rosentiel

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  1. J. Göppert
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  2. W. Rosentiel
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Göppert, J., Rosentiel, W. The Continuous Interpolating Self-organizing Map. Neural Processing Letters 5, 185–192 (1997). https://doi.org/10.1023/A:1009694727439

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  • DOI: https://doi.org/10.1023/A:1009694727439

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