在芯片上实现了模拟算法对印刷电路板的一些布局误差进行光学检测

K. Tomordi, P. Foldesy, P. Szolgay
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引用次数: 3

摘要

印刷电路板布局检测方法大多基于局部几何信息,因此它们非常适合于细胞神经网络(CNN)范式。在CNN芯片原型系统(CCPS)和CNN引擎板(CNNEB)上工作的20*22 CNN通用机(CNNUM)芯片上测试了断线、断线和隔离宽度违规以及“H”型短路检测器模拟算法,并将结果与商用检测系统进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the chip implementation of analogic algorithms for optical detection of some layout errors of printed circuit boards
Printed circuit board layout inspection methods are mostly based on local geometric information, therefore they are well suited to the cellular neural networks (CNN) paradigm. The wire break, the wire and isolation width violation and an "H" type short circuits detector analogic algorithms were tested on a 20*22 CNN Universal Machine (CNNUM) chip working in the CNN Chip Prototyping System (CCPS) and on the CNN Engine Board (CNNEB), and the results were compared to the commercially available inspection systems.
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