基于模糊逻辑理论和人工神经元网络，提出了将模糊神经网络应用于变压器故障诊断的方法。
Based on fuzzy logic theory and artificial neural networks, the method of the transformer fault diagnosis with fuzzy neural networks is presented.
剖析二进神经元的逻辑意义对二进神经网络的规则提取是十分重要的。
For extracting rules from binary neural networks, it is important to analyze logical meaning of neurons.
模糊逻辑的基本与、或、非运算分别由一个模糊神经元实现。
The realization of the basic And, Or and Negation fuzzy logical operations is shown by the fuzzy neuron.
二进神经网络的知识提取需要了解每个神经元的逻辑意义。
It is necessary to know the logical meaning of every binary neuron when extracting knowledge from a binary neural network.
提出的一种模糊神经元网络是模糊逻辑的一种网络结构的实现。
A fuzzy neural network is presented. It is essentially a network implementation of fuzzy logic.
此外，既然所有的神经元的连接和分享原理都大同小异，这种简单逻辑可以重复和放大。
Moreover, such a simple logic can be iterated and amplified, since all neurons work on a similar principle of connecting and sharing.
采用模糊逻辑和神经元网络控制策略，设计了新的控制算法来解决阀控马达控制问题。
By using the control strategies of fuzzy logic and neural networks, a new control algorithm was designed to solve the control problems.
在讨论数字逻辑与神经元的关系后，提出一种利用前向三层神经网络实现任意布尔逻辑的设计方案。
After discussing the connection between digital logic and a neuron, a strategy of implementing arbitrary Boolean logic using three layers feedforward neural network is presented.
在讨论数字逻辑与神经元的关系后，提出一种利用前向三层神经网络实现任意布尔逻辑的设计方案。
After discussing the connection between digital logic and a neuron, a strategy of implementing arbitrary Boolean logic using three layers feedforward neural network is presented.
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