37. A pattern recognition system comprising: a memory having stored therein a set of categories of training input patterns received from a plurality of subject classes during a training operation, each category having a category definition according to training input patterns received within the category, and each category being associated with a training histogram of the training input patterns received within the category, the training histogram including counts of training input patterns received for each class within the category; and a classifier that receives during a testing operation at least one test input pattern from the subject, that accesses the set of categories and computes a correlation between a category definition and each test input pattern, that forms a category association between each test input pattern and a category based on the correlation and that forms an observation histogram to classify the subject, the observation histogram being formed from each training histogram of each category of each category association and representing counts of training input patterns received by the training subsystem during the training operation, classification of the subject being determined by a peak class of the observation histogram, the peak class having the highest training input pattern count of the observation histogram.
37. A pattern recognition system comprising: a memory having stored therein a set of categories of training input patterns received from a plurality of subject classes during a training operation, each category having a category definition according to training input patterns received within the category, and each category being associated with a training histogram of the training input patterns received within the category, the training histogram including counts of training input patterns received for each class within the category; and a classifier that receives during a testing operation at least one test input pattern from the subject, that accesses the set of categories and computes a correlation between a category definition and each test input pattern, that forms a category association between each test input pattern and a category based on the correlation and that forms an observation histogram to classify the subject, the observation histogram being formed from each training histogram of each category of each category association and representing counts of training input patterns received by the training subsystem during the training operation, classification of the subject being determined by a peak class of the observation histogram, the peak class having the highest training input pattern count of the observation histogram. 38. The pattern recognition system of claim 37 wherein the set of categories includes a category labelled as unknown such that the subject can be classified as unknown.