基于鲁棒二值前馈神经网络的逻辑规则提取

ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344) Pub Date : 1998-10-12 DOI:10.1109/ICOSP.1998.770873

Zhang Junying, Bao Zheng

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摘要

本文在鲁棒二值前馈神经网络(鲁棒bnn)的连接权为- 1,0或+1的基础上，指出从鲁棒bnn中提取逻辑规则比从普通前馈神经网络中提取逻辑规则要容易得多。提出鲁棒神经网络是逻辑知识库、推理机和解释机的完美统一。

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Extraction of logic rules on the basis of robust binary feedforward neural networks

This paper, on the basis of the connection weights of robust binary feedforward neural networks (robust BNNs) being -1, 0 or +1, points out that the extraction of logic rules from robust BNNs is much easier than that from ordinary feedforward neural networks. It also puts forward the point that robust BNNs are a perfect unification of a logic knowledge database, an inference machine and an interpretation machine.

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ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)

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