Fragmentary Synchronization in Chaotic Neural Network and Data Mining

Authors:
Elena N. Benderskaya;Sofya V. Zhukova
Affiliations:
Faculty of Computer Science, St. Petersburg State Polytechnical University, Russia 194021;Graduate School of Management, St. Petersburg State University, Russia 199004
Venue:
HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
Year:
2009

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Abstract

This paper proposes an improved model of chaotic neural network used to cluster high-dimensional datasets with cross sections in the feature space. A thorough study was designed to elucidate the possible behavior of hundreds interacting chaotic oscillators. New synchronization type - fragmentary synchronization within cluster elements dynamics was found. The paper describes a method for detecting fragmentary synchronization and it's advantages when applied to data mining problem.