Neural Network Clustering Based on Distances Between Objects

  • Leonid B. Litinskii
  • Dmitry E. Romanov
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4132)


We present an algorithm of clustering of many-dimensional objects, where only the distances between objects are used. Centers of classes are found with the aid of neuron-like procedure with lateral inhibition. The result of clustering does not depend on starting conditions. Our algorithm makes it possible to give an idea about classes that really exist in the empirical data. The results of computer simulations are presented.


Lateral Inhibition Optimal Partition Input Point Close Class Noisy Point 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Leonid B. Litinskii
    • 1
  • Dmitry E. Romanov
    • 1
  1. 1.Institute of Optical-Neural Technologies Russian Academy of SciencesMoscow

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