Literature DB >> 10991338

Clustering data by inhomogeneous chaotic map lattices.

L Angelini1, F De Carlo, C Marangi, M Pellicoro, S Stramaglia.   

Abstract

A new approach to clustering, based on the physical properties of inhomogeneous coupled chaotic maps, is presented. A chaotic map is assigned to each data point and short range couplings are introduced. The stationary regime of the system corresponds to a macroscopic attractor independent of the initial conditions. The mutual information between pairs of maps serves to partition the data set in clusters, without prior assumptions about the structure of the underlying distribution of the data. Experiments on simulated and real data sets show the effectiveness of the proposed algorithm.

Year:  2000        PMID: 10991338     DOI: 10.1103/PhysRevLett.85.554

Source DB:  PubMed          Journal:  Phys Rev Lett        ISSN: 0031-9007            Impact factor:   9.161


  2 in total

1.  Analysis of X-ray structures of matrix metalloproteinases via chaotic map clustering.

Authors:  Ilenia Giangreco; Orazio Nicolotti; Angelo Carotti; Francesco De Carlo; Gianfranco Gargano; Roberto Bellotti
Journal:  BMC Bioinformatics       Date:  2010-10-08       Impact factor: 3.169

2.  Mammographic images segmentation based on chaotic map clustering algorithm.

Authors:  Marius Iacomi; Donato Cascio; Francesco Fauci; Giuseppe Raso
Journal:  BMC Med Imaging       Date:  2014-03-25       Impact factor: 1.930

  2 in total

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