Classification system and method using combined information test

Details Classification system and method using combined information test Classification system and method using combined information test

1997-05-02

1999-12-07

Hoff, Marc S.

Data processing: measuring, calibrating, or testing

Measurement system

Statistical measurement

364150, 364194, 712222, G06F10114

Patent

active

059998938

ABSTRACT:
A classification system uses sensors to obtain information from which feaes 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.

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