On decomposition of Kleene TDDs

Y. Iguchi, Tsutomu Sasao, M. Matsuura
{"title":"On decomposition of Kleene TDDs","authors":"Y. Iguchi, Tsutomu Sasao, M. Matsuura","doi":"10.1109/ATS.1997.643964","DOIUrl":null,"url":null,"abstract":"Kleene-TDDs are useful for evaluating logic functions in the presence of unknown inputs, 0 or 1. Although Kleene-TDD-based logic simulation is promising, the size of Kleene-TDD for an n-variable function is O(3/sup n//n). Thus, when n is large, the Kleene-TDDs are often too large to build. In this paper, we propose several methods to decompose Kleene-TDDs. By using this method, we can generate smaller Kleene-TDDs for sub-functions independently to reduce the necessary memory. Preliminary experimental results show that the effectiveness of the presented approach.","PeriodicalId":330767,"journal":{"name":"Proceedings Sixth Asian Test Symposium (ATS'97)","volume":"127 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings Sixth Asian Test Symposium (ATS'97)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ATS.1997.643964","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

Kleene-TDDs are useful for evaluating logic functions in the presence of unknown inputs, 0 or 1. Although Kleene-TDD-based logic simulation is promising, the size of Kleene-TDD for an n-variable function is O(3/sup n//n). Thus, when n is large, the Kleene-TDDs are often too large to build. In this paper, we propose several methods to decompose Kleene-TDDs. By using this method, we can generate smaller Kleene-TDDs for sub-functions independently to reduce the necessary memory. Preliminary experimental results show that the effectiveness of the presented approach.
Kleene tdd的分解研究
kleene - tdd对于在未知输入0或1存在的情况下评估逻辑函数很有用。虽然基于Kleene-TDD的逻辑仿真很有前景,但对于n变量函数,Kleene-TDD的大小为O(3/sup n//n)。因此,当n较大时,kleene - tdd通常太大而无法构建。本文提出了几种分解kleene - tdd的方法。使用这种方法,我们可以为子函数独立生成更小的kleene - tdd,从而减少所需的内存。初步实验结果表明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信