1. A learning method of a neural network comprising: inputting first vector rows representing data to a data input layer; inputting second vector rows as a first instructor signal to a first output layer, the first instructor signal comprising vector rows input to the data input layer at a time after inputting the first vector rows; and inputting a definite meaning as a second instructor signal to a second output layer, the second instructor signal being determined in accordance with vector rows input to the data input layer at times before and after the first vector rows are input to the data input layer, and performing learning for the data by having a plurality of first vector rows represent the definite meaning.