Patent ID: 6021383
Filing Date: 2000-02-01
Classification: G06F,G06K

Abstract:
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 s.sub.i =1, 2 . . . q to each data point v.sub.i,(b) identifying neighbors of each point v.sub.i according to a selected criterion,(c) determining the Hamiltonian 'H and determining the interaction J.sub.ij between neighboring points v.sub.i and v.sub.j,(2) locating a super-paramagnetic phase of the data set using the Monte Carlo procedure to determine susceptibility .chi.(T) by(a) determining the thermal average magnetization (m) for different temperatures,(b) identifying the presence of a super-paramagnetic phase using susceptibility .chi.,(3) determining the spin--spin correlation G.sub.if for all neighboring points v.sub.i and v.sub.j,(4) constructing data clusters using the spin--spin correlation G.sub.ij 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.