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中文摘要：
自从格兰杰提出因果关系的概念之后，格兰杰因果关系在构造神经网络的结构方面的应用越来越广泛，因为它可以得到神经网络的一个有向图。对于只有两个神经元的神经元网络，可以用通常的格兰杰因果关系去分析它们谁是因，谁是果。对于三个神经元以上的神经网络，由于神经元之间存在间接的作用，就不能象对两个神经元直接运用格兰杰因果关系去研究它们之间的结构了，而要用偏相关因果关系进行分析。论文介绍了偏相关因果关系的基本概念，并对一个模拟的三个神经元的网络比较了格兰杰因果关系和偏相关因果关系的区别。
英文摘要：
Since Granger have put forward the notation of causality,the application of Granger causality in the construction of the structure of neural network has become more and more extensive,we can get a graph with direction from them.For a network with two neurons,can analyze who is the cause and who is the result by using ordinary Granger causality.For a network with more than three neurons,can＇t analyze it with the ordinary Granger causality,for there exists indirect effect between them.We should analyze it with partial causality.This paper introduces the basic notation of partial causality,and also compare the difference between ordinary Granger causality and partial causality in a simulative network with three neurons.
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