公开(公告)号：JPH08115310A

公开(公告)日：1996-05-07

申请号：JP31386194

申请日：1994-12-16

Applicant: KOREA ELECTRONICS TELECOMM

Inventor： GO SOUKUN

IPC: G06F15/18 ,  G06N3/08

Abstract: PURPOSE: To obtain a new error function for improving the algorithm performance for learning the reverse propagation of a multilayered perceptron. CONSTITUTION: When a learning pattern x=(x1 , x2 ,..., xNO) is inputted to a multilayered perceptron composed of L layers, calculation is made in all directions (S1), the output error signal of an output layer is calculated (S2), the error signal of a lower layer is calculated through reverse propagation (S3), and the weighted value of respective hierarchies is changed (S4). This proposed error function reduces the occurrence of such a phenomenon that an output node is inappropriately saturated from the learning process of a neuro network by generating a strong error signal when the difference between the target value and output value of the output layer becomes larger. When the target value approaches the output value, the error function prevents the neuro network from excessively learning the learning pattern by generating a weak error signal.