Classification System and Method Using Combined Information Testing
Patent, Filed 2 May 1997, patented 7 Dec 1999
DEPARTMENT OF THE NAVY WASHINGTON DC
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A classification system uses sensors to obtain information from which features which characterized a source or object to classified can be extracted. The features are extracted from the information and compiled into a feature vector which is then quantized to one of one of M discrete symbols. After N feature vectors have been quantized, a test vector having components which are defined by the number of occurrences of each of the M symbols in N the quantized vectors is built. The system combines the test vector with training data to simultaneously estimate symbol probabilities for each class and classify the test vector using a decision rule that depends only on the training and test data. The system classifies the test vector using either a Combined Bayes test or a Combined Generalized likelihood ratio test.