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    請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/77474

    題名: 叢集式壓縮資料對未知向量之X填入法
    其他題名: Usage cluster analysis for filling methodology of unknowns for efficient compaction
    作者: 魏子翔;Wei, Tsu-Hsiang
    貢獻者: 淡江大學電機工程學系碩士在職專班
    饒建奇;Rau, Jiann-chyi
    關鍵詞: 壓縮資料;叢集;X-fill;ATE Vector;Compression;Cluster
    日期: 2012
    上傳時間: 2012-06-21 06:48:28 (UTC+8)
    摘要: 在現今的IC測試領域中,因為電路設計的複雜度越來越高,使得測試資料與日俱增,而在測試資料當中,未知向量又會占去大部分的測試容量及空間,不但浪費時間,佔去測試時的資料空間,更進一步影響資料壓縮率,造成測試者的負擔。
    本文章內容,是利用叢集式壓縮法,在未知向量上,加上X填入法,使得整個壓縮率得以提升,解決一般測試者對未知向量的困擾,我們將叢集式壓縮法先做Group的分類,再以Cluster Number =2的情況下,對未知向量做固定值的填入(遮罩),如此得以改善壓縮率,也因未知向量視為固定值,減少了壓縮資料失真的問題。
    One of IC tester’s problems is the larger and larger test data volume due to the complexity of the circuit design. Furthermore, since the unknown generated during the test procedure is taking a major part of the test data volume and space, it has become a waste of time and a burden, affecting rate of data compact.

    In this study, we combine clustering-approach with filling in X to substitute the unknown. By doing so, we solve the problem of the unknown and thus upgrade the compression rate. Take our case as an example, we first classify the clusters into groups and fill in a fixed number when cluster number equals 2. The outcome is a higher compression rate and no loss of data.
    顯示於類別:[電機工程學系暨研究所] 學位論文


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