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Title:
【発明の名称】神経回路網の訓練方法
Document Type and Number:
Japanese Patent JP3290984
Kind Code:
B2
Abstract:
PCT No. PCT/GB91/01967 Sec. 371 Date May 10, 1993 Sec. 102(e) Date May 10, 1993 PCT Filed Nov. 8, 1991 PCT Pub. No. WO92/09044 PCT Pub. Date May 29, 1992.A method of training a neural network (2) having dynamically adjustable parameters controlled by a controller (10) which determine the response of the network (2). A set of input vectors (Il to In) are input to network (2) at an input port (4). The corresponding set of output vectors (O'l to O'n) provided by the network (2) are compared to a target set of output vectors (Ol to On) by an error logger (12) which provides to the controller (10) a measure of similarity of the two sets. The controller (10) is arranged to alter the dynamic parameters independence on the average number of occasions the output vectors are different from the respective target output vectors. Measuring the similarity of the whole of the output set and target set and adjusting the parameters on this global measure rather than on the similarity of pairs of individual vectors provides enhanced training rates for neural networks having a data throughput rate that can be higher than the rate at which the parameters can be adjusted.

Inventors:
Wood, David Charles
Application Number:
JP51819291A
Publication Date:
June 10, 2002
Filing Date:
November 08, 1991
Export Citation:
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Assignee:
British Telecommunications Public Limited Company
International Classes:
G06F15/18; G06G7/60; G06N3/067; G06N3/08; G06N99/00; (IPC1-7): G06N3/08
Other References:
S.Kirkpatric,et.al.,”Optimization by Simulated Annealing”,SCIENCE,Vol.220,No.4598,1983,,pp.671−680
蔵富靖規・他,「学習機能を実現した光連想メモリ」,テレビジョン学会技術研究報告,日本,社団法人テレビジョン学会・発行,1990年10月26日,Vol.14,No.58,pp.19−24,特許庁CSDB文献番号:CSNT199901593002
鎌田洋,「ニューロンの非線形性を適応的に制御する誤差逆電播学習法」,電子情報通信学会技術研究報告,日本,社団法人電子情報通信学会・発行,1990年10月19日,Vol.90,No.262(NC90−30〜41),pp.9−14,特許庁CSDB文献番号:CSNT199900023002
Attorney, Agent or Firm:
Takehiko Suzue (3 outside)