SOFT CLUSTERING ALGORITHM BASED ON SEPARATING HYPERSURFACES

Authors

  • О. І. Chumachenko National Technical University of Ukraine “Ihor Sikorsky Kyiv Polytechnic Institute”
  • V. S. Gorbatiuk National Technical University of Ukraine “Ihor Sikorsky Kyiv Polytechnic Institute”

DOI:

https://doi.org/10.18372/1990-5548.52.11860

Keywords:

Clustering, artificial neural networks, soft clustering, nonlinear optimization.

Abstract

A new “soft” clustering algorithm is proposed based on the use of artificial neural networks as  models of hypersurfaces that separate clusters. The algorithm allows to solve the problem of soft clusterization as a problem of smooth nonlinear function optimization and, therefore, to apply the entire mathematical apparatus of nonlinear optimization, which has evolved significantly in recent years. 

Author Biographies

О. І. Chumachenko, National Technical University of Ukraine “Ihor Sikorsky Kyiv Polytechnic Institute”

Technical Cybernetic Department

Candidate of Science (Engineering). Assosiate Professor.

V. S. Gorbatiuk, National Technical University of Ukraine “Ihor Sikorsky Kyiv Polytechnic Institute”

Post-graduate student

References

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Teuvo Kohonen, Self-Organized Formation of Topologically Correct Feature Maps. Biological Cybernetics. 1982, 43 (1): 59–69.

Warren McCulloch, and Walter Pitts, A Logical Calculus of Ideas Immanent in Nervous Activity. Bulletin of Mathematical Biophysics. 1943, 5 (4): 115–133.

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Christopher M. Bishop, Pattern Recognition and Machine Learning. Springer. 2006.

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How to Cite

Chumachenko О. І., & Gorbatiuk, V. S. (2017). SOFT CLUSTERING ALGORITHM BASED ON SEPARATING HYPERSURFACES. Electronics and Control Systems, 2(52), 11–15. https://doi.org/10.18372/1990-5548.52.11860

Issue

Vol. 2 No. 52 (2017)

Section

THEORY AND METHODS OF SIGNAL PROCESSING

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