改进了随机测试中特征分析混叠的边界

N. Saxena, P. Franco, E. McCluskey
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引用次数: 9

摘要

在以前的工作中,我们推导了长度为L的随机测试模式在序列签名分析中混叠概率的一个简单界~+2。这个简单的边界在这里几乎是原来的2倍。对于串行签名分析,表明当测试长度L小于签名多项式的周期Lc时,I+& 1混叠概率的上界为- = L (E L小,L大)。推导出的简单边界与精确的混叠概率值以及实验测量的混叠概率值进行了比较。推测L-l是序列签名混叠概率的最佳单调界。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
REFINED BOUNDS ON SIGNATURE ANALYSIS ALIASING FOR RANDOM TESTING
in previous work a simple bound, ~+2 , on the aliasing probability in serial signature analysis for a random test pattern of length L was derived. This simple bound is sharpened here by almost a factor of two. For serial signature analysis, it is shown that the I+& 1 aliasing probability is bounded above by - = L (E L small for large L) for test lengths L less than the period, Lc, of the signature polynomial. The simple bounds derived are compared with exact as well as experimentally measured aliasing probability values. It is conjectured that L-l is the best monotonic bound on the aliasing probability for serial signature analysis.
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