The printed circuit board layout inspection methods are mostly based on local geometric information, therefore it is well suited to the cellular neural network (CNN) paradigm. Two layout errors are detected here namely, the breaks in the wires and some kind of short circuits. The designed analogic algorithms to solve the problems above were tested on real life examples using an experimental system based on our CNN-HAC1M digital multiprocessor add-on-board, with 1 million cell space and 2.0 /spl mu/s/cell/iteration speed.
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机译：印刷电路板布局检查方法主要基于局部几何信息，因此非常适合于细胞神经网络（CNN）范例。在此检测到两个布局错误，即导线断裂和某种短路。使用基于我们的CNN-HAC1M数字多处理器附加板的实验系统，以一百万个单元空间和2.0 / spl mu / s / cell /迭代速度的实验系统，在现实生活中的示例上测试了解决上述问题的设计类比算法。 。
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