Optimizing method of learning data set for signal discrimination apparatus and signal discrimination apparatus capable of optimizing learning data set by using a neural network
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United States of America Patent
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Nov 9, 2010
Grant Date -
Sep 24, 2009
app pub date -
Aug 2, 2007
filing date -
Aug 3, 2006
priority date (Note) -
Expired
status (Latency Note)
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Abstract
A method of the present invention is processed by a selector. The selector selects each member constituting a learning data set from a data set source. Each member of the source is feature data extracted through a transducer and assigned to any one of categories in advance. The selector calculates each member's divergence degree of the source to obtain an average divergence degree. If an output neuron of the output layer of a neural network is related to different categories of all the categories represented by the output layer, the selector includes every member of the source corresponding to the category of the minimum average divergence degree in the selection from the source to the learning data set. The selector also excludes, from the selection, every member of the source corresponding to every remaining category of the different categories.
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