Data processing: artificial intelligence – Neural network – Structure
Reexamination Certificate
2006-01-03
2006-01-03
Starks, Wilbert L. (Department: 2129)
Data processing: artificial intelligence
Neural network
Structure
C706S026000, C706S027000
Reexamination Certificate
active
06983265
ABSTRACT:
A method is described to improve the data transfer rate between a personal computer or a host computer and a neural network implemented in hardware by merging a plurality of input patterns into a single input pattern configured to globally represent the set of input patterns. A base consolidated vector (U′*n) representing the input pattern is defined to describe all the vectors (Un, . . . , Un+6) representing the input patterns derived thereof (U′n, . . . , U′n+6) by combining components having fixed and ‘don't care’ values. The base consolidated vector is provided only once with all the components of the vectors. An artificial neural network (ANN) is then configured as a combination of sub-networks operating in parallel. In order to compute the distances with an adequate number of components, the prototypes are to include also components having a definite value and ‘don't care’ conditions. During the learning phase, the consolidated vectors are stored as prototypes. During the recognition phase, when a new base consolidated vector is provided to ANN, each sub-network analyses a portion thereof After computing all the distances, they are sorted one sub-network at a time to obtain the distances associated to each vector.
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de Tremiolles Ghislain Imbert
Tannhof Pascal
Schnurmann H. Daniel
Starks Wilbert L.
Tran Mai T.
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