Patent ID: 7039621

Claim:
A method of mapping a set of n-dimensional input patterns to an m-dimensional space for display of said patterns using locally defined neural networks, comprising the steps of: (a) creating a set of locally defined neural networks trained according to a mapping of a subset of the n-dimensional input patterns into an m-dimensional output space; and (b) mapping additional n-dimensional input patterns using the locally defined neural networks wherein step (a) comprises the steps of: (i) selecting k patterns from the subset of n-dimensional input patterns, {x i , i=1, 2, . . . k, x i ∈R n }; (ii) mapping the patterns {x i } into an m-dimensional space (x i →y i , i=1, 2, . . . k, y i ∈R m ), to form a training set T={(x i , y i ), i=1, 2, . . . k}; (iii) determining c n-dimensional reference points, {(c i ; i=1, 2, . . . c, c i ∈R n }; (iv) partitioning T into c disjoint clusters C j based on a distance function d, {C j ={(x i , y i ): d(x i , y i )≦d(x i , c k ) for all k≠j; j=1, 2, . . . c; i=1, 2, . . . k}; and (v) training c independent local networks {Net i L , i=1, 2, . . . c}, with respective pattern subsets C i .