PURPOSE: To make a learning time relatively short and to improve a recognition ratio even if the number of correlative multivariate data (input data) to be increased.
CONSTITUTION: Sample data Xj between the sample data Xj and tutor data Yj for category classification which are set by a learning data setting device are sent to a statistical analyzing device 2 to generate decision functions Zk to be separated by plural categories, and the generated decision functions are sent to an input data converter 3. The input data converter 3 calculates the inner product of the given decision functions and deletes similar functions except one when the functions are similar. Calculation results (less than multivariate data) obtained by substituting multivariate data Y and W, sent from the learning data setting device 1 and recollection data setting device 4, in the finally left decision function are inputted to the input layer of the neural network formed on an NN analyzing device 5.
FUJII TORU
USHIDA HIROHIDE
TSUTSUMI YASUHIRO
IRIE ATSUSHI
