1. A system of pattern recognition using feature vectors representing corresponding portions of a physical pattern, said system comprising: means for assigning a class to every training feature vector within a set of training feature vectors; means for nonlinearly mapping the set of feature vectors to a higher dimensional space; means for separating the classes by computing a projection which maximally separates the classes in the higher dimensional space and projecting each of the training feature vectors; means for assigning the training feature vectors having projections less than a first threshold to a first memory segment and remaining training feature vectors into a second memory segment; means for storing the hyperplane and the first threshold within the first and second memory segments; means for separating the classes within the first and/or second memory segments if the classes are associated with a number of training feature vectors greater than a second threshold; means for designating in a memory the first and/or second memory segments as terminal memory segments if said first and/or second memory segments contain classes associated with a number of training feature vectors less than the second threshold; means for storing information about the classes associated with the number of training feature vectors less than the second threshold within corresponding terminal memory segments; and means for recognizing a portion of the physical pattern by retrieving stored information from one or more terminal memory segments corresponding to one or more feature vectors representing said portion.