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Kernel Fuzzy Kohonen’s Clustering Neural Network and It’s Recursive Learning

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Abstract

The architecture of multilayer kernel clustering neuro-fuzzy system and algorithm of its self-learning are intended for the recovery of overlapped clusters in situations when the streams of observations are fed in the online mode is proposed. The designed system, based on the T. Kohonen’s self-organizing map, permits to recover linearly nonseparated data classes, processes information in an online mode, doesn’t suffer from the “curse of dimensionality” and is easy in implementation.

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Authors and Affiliations

  1. Kharkiv National University of Radio Electronics, Kharkiv, 61166, Ukraine

    Ye. V. Bodyanskiy, A. O. Deineko & F. M. Eze

Authors
  1. Ye. V. Bodyanskiy
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  2. A. O. Deineko
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  3. F. M. Eze
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Correspondence to A. O. Deineko.

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Bodyanskiy, Y.V., Deineko, A.O. & Eze, F.M. Kernel Fuzzy Kohonen’s Clustering Neural Network and It’s Recursive Learning. Aut. Control Comp. Sci. 52, 166–174 (2018). https://doi.org/10.3103/S0146411618030045

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  • DOI: https://doi.org/10.3103/S0146411618030045

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