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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

A Mathematical Study of the Rule Extraction of a 3-layered Feed-forward Neural Networks

林志忠, Lin, Chih-chung Unknown Date (has links)
對於神經網路系統將提出一個法則萃取的方式,並從神經網路中得到相關法則。在這裡我們所提到的方法是根據反函數的觀念而得到的。 / A rule-extraction method of the layered feed-forward neural networks is proposed here for identifying the rules suggested in the network. The method that we propose for the trained layered feed-forward neural network is based on the inversion of the functions computed by each layer of the network. The new rule-extraction method back-propagates regions from the output layer back to the input layer, and we hope that the method can be used further to deal with the predicament of ANN being a black box.

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