它测试ASCII等价性，因此1将不等于1.0，即使它们有相同的数值。

This tests ASCII equivalence, so 1 will not be equal to 1.0, even though they have the same numeric value.

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同时证明了属性神经网络与属性坐标系的等价性，从而为属性推理提供可操作的数值推导方法。

The equivalence of attribute neural networks and attribute coordinate space is proved, and a method of numerical value inference is provided for attribute inference.

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给出的典型数值计算结果证实了这种方法与有限拉盖尔·高斯函数展开法是等价的。

Typical numerical examples have been given, showing the equivalence of this method and the finite Laguerre Gauss function expansion.

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