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Improved critical area prediction by application of pattern recognition techniques

机译:通过应用模式识别技术改进了临界区域预测

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A novel technique to predict the susceptibility of VLSIC layouts to particle-induced failure is presented. The investigation applies the concept of Critical Areas to determine the failure probability of rectilinear layouts. A unique methodology has been devised, with which the relationship between the recurrent patterns observed within the topology of a layout and the robustness of the design against particulate contamination can be quantified. The critical area is formulated as a function of the dimensions of the identifiable geometrical shapes and the characteristics of the defect model. In comparison with current approximation methods, the proposed technique is quick, exact, adaptable for different defect models and guarantees computational accuracy irrespective of layout complexity.
机译:提出了一种预测VLSIC布局对粒子诱导的故障的易感性的新技术。调查适用于关键区域的概念来确定直线布局的失效概率。已经设计了一种独特的方法,其中可以量化在布局拓扑和颗粒污染的设计的拓扑中观察到的复发模式之间的关系。作为可识别的几何形状的尺寸和缺陷模型的特性,将临界区域配制成函数。与电流近似方法相比,所提出的技术快速,精确,适用于不同的缺陷模型,而不管布局复杂程度如何保证计算精度。

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