PURPOSE: To shorten a learning time in a neural network learning device.

CONSTITUTION: In a neural network NW in which at least one hidden layer is provided between an input layer and an output layer, each layer is constituted of plural pieces of units, and also, in each layer, there is no coupling, and between the layers, the units are coupled by a certain weight coefficient, and that which performs a non-linear or linear function to that which takes the sum total by multiplying an output of the pre-stage layer by a weight coefficient becomes an output of each unit, outputs of the hidden layer and the output layer, and a target value by a teacher signal corresponding thereto are compared, and whether an error between the output of the unit of its layer and the target value by the teacher signal is eliminated or not is decided by an output value decided part (E), and in the case it is decided that the error is eliminated, a calculation of a variation of weight of coupling to other unit connected to its specific unit is stopped thereafter, and weight updating is not executed.