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Method and apparatus for clustering data

  • US 6,021,383 A
  • Filed: 10/07/1996
  • Issued: 02/01/2000
  • Est. Priority Date: 10/07/1996
  • Status: Expired due to Fees
First Claim
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1. A method for analyzing signals containing a data set which is representative of a plurality of physical phenomena, to identify and distinguish among said physical phenomena by determining clusters of data points within said data set, said method comprising:

  • (1) constructing a physical analog Potts-spin model of the data set by(a) associating a Potts-spin variable si =1, 2 . . . q to each data point vi,(b) identifying neighbors of each point vi according to a selected criterion,(c) determining the Hamiltonian '"'"'H and determining the interaction Jij between neighboring points vi and vj,(2) locating a super-paramagnetic phase of the data set using the Monte Carlo procedure to determine susceptibility χ

    (T) by(a) determining the thermal average magnetization (m) for different temperatures,(b) identifying the presence of a super-paramagnetic phase using susceptibility χ

    ,(3) determining the spin--spin correlation Gif for all neighboring points vi and vj,(4) constructing data clusters using the spin--spin correlation Gij within the super-paramagnetic phase located in step (2) to partition the data set, and(5) identifying said physical phenomena based on said data clusters.

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