Pattern recognition
First Claim
1. A method for pattern recognition, comprising:
- forming a sequence of feature vectors from a digitized incoming signal, said feature vectors comprising feature vector components,comparing at least one feature vector with templates of candidate patterns by computing a distortion measure including distortion measure contributions,formulating a control signal based on at least one time-dependent variable of the recognition process, andfor said at least one feature vector, computing only a subset of said distortion measure contributions using the vector components of said at least one feature vector, said subset being chosen in accordance with said control signal.
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Accused Products
Abstract
Pattern recognition, wherein a sequence of feature vectors is formed from a digitized incoming signal, the feature vectors comprising feature vector components, and at least one feature vector is compared with templates of candidate patterns by computing a distortion measure. A control signal based on at least one time-dependent variable of the recognition process is formulated, and the distortion measure is computed using only a subset of the vector components of the feature vector, the subset being chosen in accordance with said control signal. This reduces the computational complexity of the computation, as the dimensionality of the vectors involved in the computation is effectively reduced. Although such a dimension reduction decreases the computational need, it has been found not to significantly impair the classification performance.
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Citations
23 Claims
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1. A method for pattern recognition, comprising:
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forming a sequence of feature vectors from a digitized incoming signal, said feature vectors comprising feature vector components, comparing at least one feature vector with templates of candidate patterns by computing a distortion measure including distortion measure contributions, formulating a control signal based on at least one time-dependent variable of the recognition process, and for said at least one feature vector, computing only a subset of said distortion measure contributions using the vector components of said at least one feature vector, said subset being chosen in accordance with said control signal. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A device for pattern recognition, comprising:
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means for forming a sequence of feature vectors from a digitized incoming signal, a control module adapted to formulate a control signal based on at least one time-dependent variable of the recognition process, and means for comparing at least one feature vector with templates of candidate patterns by computing a distortion measure comprising distortion measure contributions, wherein said comparing means are arranged to compute only a subset of the distortion measure contributions, said subset being chosen in accordance with said control signal. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20)
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21. A system for pattern recognition comprising:
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means for forming a sequence of feature vectors from a digitized incoming signal, a control module adapted to formulate a control signal based on at least one time-dependent variable of the recognition process, and means for comparing at least one feature vector with templates of candidate patterns by computing a distortion measure comprising distortion measure contributions, wherein said comparing means are arranged to compute only a subset of the distortion measure contributions, said subset being chosen in accordance with said control signal.
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22. A computer program product, directly loadable into the memory of a computer, comprising computer program code means for performing, when executed on the computer, the steps of:
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forming a sequence of feature vector from a digitized incoming signal, said feature vectors comprising feature vector components, comparing at least one feature vector with templates of candidate patterns by computing a distortion measure including distortion measure contributions, formulating a control signal based on at least one time-dependent variable of the recognition process, and for said at least one feature vector, computing only a subset of said distortion measure contributions using the vector components of said at least one feature vector, said subset being chosen in accordance with said control signal. - View Dependent Claims (23)
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Specification