Clustering by Chaotic Neural Networks with Mean Field Calculated Via Delaunay Triangulation

High quality clustering is impossible without a priori information about clustering criteria. The paper describes the development of new clustering technique based on chaotic neural networks that overcomes the indeterminacy about number and topology of clusters. Proposed method of weights computation via Delaunay triangulation allows to cut down computing complexity of chaotic neural network clustering.

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