Signal pattern recognition apparatus comprising parameter training controller for training feature conversion parameters and discriminant functions
First Claim
1. A signal pattern recognition apparatus for classifying an inputted signal pattern into one of a plurality of predetermined classes so as to recognize the inputted signal pattern, comprising:
- a plurality of feature transformation means for respectively transforming the inputted signal pattern into vectors in a plurality of feature spaces corresponding respectively to said classes by executing a feature transformation process by means of a predetermined transformation parameter corresponding to each of said classes so as to emphasize a feature of each of said classes, said feature transformation means being provided respectively for said plurality of classes;
a plurality of discriminant function means for respectively calculating a value of a discriminant function by means of a predetermined discriminant function representing a similarity measure of each of said classes for said vectors in said plurality of feature spaces which are transformed by said plurality of feature transformation means, said discriminant function means being provided respectively for said plurality of classes;
selection means for executing a signal pattern recognition process by selecting a class to which the inputted signal pattern belongs based on the values of said plurality of discriminant functions corresponding respectively to said classes, said discriminant functions being obtained through said calculation executed by said plurality of discriminant function means; and
training control means for training and setting said plurality of transformation parameters of said feature transformation process and said plurality of discriminant functions, so that an error probability of said signal pattern recognition is minimized based on a predetermined training signal pattern.
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Abstract
In a signal pattern recognition apparatus, a plurality of feature transformation sections respectively transform an inputted signal pattern into vectors in a plurality of feature spaces corresponding respectively to predetermined classes using a predetermined transformation parameter corresponding to each of the classes so as to emphasize a feature of each of the classes, and a plurality of discriminant function sections respectively calculates a value of a discriminant function using a predetermined discriminant function representing a similarity measure of each of the classes for the transformed vectors in the plurality of feature spaces. Then, a selection section executes a signal pattern recognition process by selecting a class to which the inputted signal pattern belongs based on the calculated values of a plurality of discriminant functions corresponding respectively to the classes, and a training control section trains and sets a plurality of transformation parameters of the feature transformation process and a plurality of discriminant functions so that an error probability of the signal pattern recognition is minimized based on a predetermined training signal pattern.
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Citations
16 Claims
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1. A signal pattern recognition apparatus for classifying an inputted signal pattern into one of a plurality of predetermined classes so as to recognize the inputted signal pattern, comprising:
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a plurality of feature transformation means for respectively transforming the inputted signal pattern into vectors in a plurality of feature spaces corresponding respectively to said classes by executing a feature transformation process by means of a predetermined transformation parameter corresponding to each of said classes so as to emphasize a feature of each of said classes, said feature transformation means being provided respectively for said plurality of classes; a plurality of discriminant function means for respectively calculating a value of a discriminant function by means of a predetermined discriminant function representing a similarity measure of each of said classes for said vectors in said plurality of feature spaces which are transformed by said plurality of feature transformation means, said discriminant function means being provided respectively for said plurality of classes; selection means for executing a signal pattern recognition process by selecting a class to which the inputted signal pattern belongs based on the values of said plurality of discriminant functions corresponding respectively to said classes, said discriminant functions being obtained through said calculation executed by said plurality of discriminant function means; and training control means for training and setting said plurality of transformation parameters of said feature transformation process and said plurality of discriminant functions, so that an error probability of said signal pattern recognition is minimized based on a predetermined training signal pattern. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 13, 14, 15)
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9. A method for classifying an inputted signal pattern into one of a plurality of predetermined classes so as to recognize the inputted signal pattern, including the following steps of:
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transforming the inputted signal pattern into vectors in a plurality of feature spaces corresponding respectively to said classes by executing a feature transformation process by means of a predetermined transformation parameter corresponding to each of said classes so as to emphasize a feature of each of said classes; calculating a value of a discriminant function by means of a predetermined discriminant function representing a similarity measure of each of said classes for said vectors in said plurality of feature spaces which are obtained through said feature transformation process; executing a signal pattern recognition process by selecting a class to which the inputted signal pattern belongs based on the calculated values of said plurality of discriminant functions corresponding respectively to said classes; and training and setting the transformation parameter of said feature transformation process and each of said discriminant functions, so that an error probability of said signal pattern recognition is minimized based on a predetermined training signal pattern. - View Dependent Claims (10, 11, 12, 16)
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Specification