Method for learning neural net

Abstract

Abstract PURPOSE:To improve the accuracy of high output selected by a candidate selecting means out of plural outputs by multiplying an error calculated from the output of a neural net and similarity by a term to be increased/decreased in accordance with the size of the similarity and minimizing the multiplied value as an error function. CONSTITUTION:In this learning method, a feature vector is inputted and similarity to plural categories is outputted. An error calculated from the output of the neural net and the similarity is multiplied by the term to be increased/ decreased in accordance with the size of the similarity and the multiplied result is used as an error function and minimized. Namely in the flow chart of a neural net learning procedure, an error adjusting step 14 is added to a convensional learning method. In the step 14, an error calculated by error calculation between the output value of a step 13 and a teaching signal is multiplied by an error function to adjust the error due to the size of similarity. Thus the highly accurate collating result of pattern information can be obtained.

Inventors

• 👤 Yoshimasa Koike
• 👤 義昌 小池
• 👤 Masaaki Tanabe
• 👤 田辺　雅秋

Bibliographic Details