首页> 外文会议>IEEE European Test Symposium >M-S specification binning based on digitally coded indirect measurements
【24h】

M-S specification binning based on digitally coded indirect measurements

机译:基于数字编码间接测量的M-S规格分档

获取原文

摘要

Binning of IC circuits after volume fabrication is widely used to separate tested circuits in different classes depending on different degrees of specifications compliance. When the specifications are directly measured, the boundaries of the classes are usually linear functions in the specification space. For alternate testing strategies the indirect measures generate more complicated regions in the measure space due to the non linear mapping between the specification space and the measure space. The binning strategy proposed in this paper works with the same efficiency regardless of the shape of the boundaries of each binning region. A digital encoding of the measure space using octrees is the key idea of the proposal. The strategy has two phases: (1) The training to generate the digital codes for the binning subsets and (2) the actual production binning of the fabricated ICs. The first phase is performed only once and requires sufficient samples of each binning class to generate the octree under realistic variations. The second phase is fast and requires only to evaluate the octree using the measures of the tested IC. In order to illustrate the proposal, the method has been applied to a Biquad filter considering three specification bins as a proof of concept. Successful simulation results are reported showing considerable advantages in terms of binning speed. In addition, the method has been compared to a SVM classifier revealing substantial benefits.
机译:批量制造后,IC电路的装箱被广泛用于根据不同程度的规范合规性将测试的电路分为不同的类别。当直接测量规格时,类别的边界通常是规格空间中的线性函数。对于替代测试策略,由于规范空间和度量空间之间的非线性映射,间接度量会在度量空间中生成更复杂的区域。本文提出的分箱策略以相同的效率工作,而不管每个分箱区域的边界形状如何。该方案的关键思想是使用八叉树对量度空间进行数字编码。该策略分为两个阶段:(1)训练以生成用于合并子集的数字代码,以及(2)所制造的IC的实际生产合并。第一阶段仅执行一次,并且需要每个分类类别的足够样本才能在实际变化下生成八叉树。第二阶段很快,只需要使用经过测试的IC的方法来评估八叉树。为了说明该建议,该方法已应用于考虑了三个规格箱的Biquad滤波器,作为概念证明。据报道,成功的仿真结果显示了装仓速度方面的显着优势。此外,该方法已与SVM分类器进行了比较,显示出了很多好处。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号