Patent ID: 8345932

Claim:
A biometric data processing system, comprising: at least one signal acquisition system for collecting biometric input; a feature extraction system for extracting feature vectors from the biometric input; and a support vector machine (SVM) having a plurality of kernel functions, wherein each kernel function is configured for mapping a feature vector to a high dimensional hyperspace structure, wherein the high dimensional hyperspace structure is defined as follows: H=Hyperspace Λ i =Sub-Universe Ω w =World φ i,j =Dimension ρ i,j =Policy δ i,j,k =Operator A l =Cluster α l,i,j =Bin Member where i=sub-universe number, j=dimension number, k=operator number, l=cluster number, m=world number, A l ={∀ l,i,j } where a cluster is defined as a set of all cluster members, each cluster member being vectored into a high dimensional space, Λ i ={∀ i,j } where a sub-universe is defined as a set of dimensions, φ i,j =∃ i,j U{∀ i,j,k } where for each dimension there exists an associated policy and a set of operators, the policy providing an association between operators or heuristics and a dimension, Ω w ={{{∀ l,i,j }ε{Λ i }}U{Λ i } where a world automaton specifies the set of all data elements which belong to all clusters within a sub-universe and the universe, H={∀Ω w } where a hyperspace automaton defines the universe of a problem domain, where each kernel function is a parametric function that projects dimensional data onto the high dimensional hyperspace structure, each kernel function including a plurality of multiple independent kernels, where k ( x,x ′)= k 1 ( x,x ′)+ k 2 ( x,x ′) . . . defines a kernel function from a summation of the plurality of multiple independent kernels.