JP2637760B

PURPOSE:To converge the learning of analog information with a high accuracy and simultaneously, at a high speed by multiplexing a neutral network, obtaining a weighted mean, making it into a final output and causing a weight coefficient between an input layer and an intermediate layer or between the intermediate layer and an output layer to be random. CONSTITUTION:The neutral network is composed of an input layer 10, an intermediate layer 12, an output layer 14, and a final output layer 16, and the intermediate layer 12 and output layer 14 are made into multistages. The weight coefficient between the input layer 10 and intermediate layer 12 or between the intermediate layer 12 and output layer 14 is made random according to a necessity, the learning is independently executed in respective stages in the multiplexed intermediate layer 12 and output layer 14, the weighted mean of the outputs of respective stages of the output layer 14 is obtained in the final output layer 16, and it is made into a final output OT. Thus, the efficient learning of the data of a read world can be executed, and the convergency can be made high-speed.