计算最小冗余前缀码的两种空间经济算法

R. Milidiú, A. Pessoa, E. Laber
{"title":"计算最小冗余前缀码的两种空间经济算法","authors":"R. Milidiú, A. Pessoa, E. Laber","doi":"10.1109/DCC.1999.755676","DOIUrl":null,"url":null,"abstract":"The minimum redundancy prefix code problem is to determine, for a given list W=[w/sub 1/,...,w/sub n/] of n positive symbol weights, a list L=[l/sub 1/,...,l/sub n/] of n corresponding integer codeword lengths such that /spl Sigma//sub i=1//sup n/2/sup -li//spl les/1 and /spl Sigma//sub i=1//sup n/w/sub i/l/sub i/ is minimized. Let us consider the case where W is already sorted. In this case, the output list L can be represented by a list M=[m/sub 1/,...,m/sub H/], where m(l/sub 1/), for l=1,...,H, denotes the multiplicity of the codeword length l in L and H is the length of the greatest codeword. Fortunately, H is proved to be O(min{log(1/(p/sub 1/)),n}), where p/sub 1/ is the smallest symbol probability, given by w/sub 1///spl Sigma//sub i=1//sup n/w/sub i/. We present the F-LazyHuff and the E-LazyHuff algorithms. F-LazyHuff runs in O(n) time but requires O(min{H/sup 2/,n}) additional space. On the other hand, E-LazyHuff runs in O(nlog(n/H)) time, requiring only O(H) additional space. Finally, since our two algorithms have the advantage of not writing at the input buffer during the code calculation, we discuss some applications where this feature is very useful.","PeriodicalId":103598,"journal":{"name":"Proceedings DCC'99 Data Compression Conference (Cat. No. PR00096)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"Two space-economical algorithms for calculating minimum redundancy prefix codes\",\"authors\":\"R. Milidiú, A. Pessoa, E. Laber\",\"doi\":\"10.1109/DCC.1999.755676\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The minimum redundancy prefix code problem is to determine, for a given list W=[w/sub 1/,...,w/sub n/] of n positive symbol weights, a list L=[l/sub 1/,...,l/sub n/] of n corresponding integer codeword lengths such that /spl Sigma//sub i=1//sup n/2/sup -li//spl les/1 and /spl Sigma//sub i=1//sup n/w/sub i/l/sub i/ is minimized. Let us consider the case where W is already sorted. In this case, the output list L can be represented by a list M=[m/sub 1/,...,m/sub H/], where m(l/sub 1/), for l=1,...,H, denotes the multiplicity of the codeword length l in L and H is the length of the greatest codeword. Fortunately, H is proved to be O(min{log(1/(p/sub 1/)),n}), where p/sub 1/ is the smallest symbol probability, given by w/sub 1///spl Sigma//sub i=1//sup n/w/sub i/. We present the F-LazyHuff and the E-LazyHuff algorithms. F-LazyHuff runs in O(n) time but requires O(min{H/sup 2/,n}) additional space. On the other hand, E-LazyHuff runs in O(nlog(n/H)) time, requiring only O(H) additional space. Finally, since our two algorithms have the advantage of not writing at the input buffer during the code calculation, we discuss some applications where this feature is very useful.\",\"PeriodicalId\":103598,\"journal\":{\"name\":\"Proceedings DCC'99 Data Compression Conference (Cat. No. PR00096)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1999-03-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings DCC'99 Data Compression Conference (Cat. No. PR00096)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DCC.1999.755676\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings DCC'99 Data Compression Conference (Cat. No. PR00096)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DCC.1999.755676","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15

摘要

最小冗余前缀码问题是确定,对于给定列表W=[W /sub 1/,…],w/下标n/]的n个正符号权值,一个列表L=[L /下标1/,…],l/下标n/]的n个对应的整数码字长度,使得/spl Sigma//下标i=1//sup n/2/sup -li//spl les/1和/spl Sigma//下标i=1//sup n/w/下标i/l/下标i/最小。让我们考虑W已经排序的情况。在这种情况下,输出列表L可以表示为列表M=[M /sub 1/,…],m/下标H/],其中m(l/下标1/),对于l=1,…,H为码字长度l在l中的多重数,H为最大码字的长度。幸运的是,H被证明为O(min{log(1/(p/下标1/)),n}),其中p/下标1/是最小的符号概率,由w/下标1///spl Sigma//下标i=1//sup n/w/下标i/给出。提出了F-LazyHuff算法和E-LazyHuff算法。F-LazyHuff运行时间为O(n),但需要O(min{H/sup 2/,n})额外空间。另一方面,E-LazyHuff在O(nlog(n/H))时间内运行,只需要O(H)额外空间。最后,由于我们的两种算法具有在代码计算期间不写入输入缓冲区的优点,因此我们讨论了一些应用程序,其中该特性非常有用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Two space-economical algorithms for calculating minimum redundancy prefix codes
The minimum redundancy prefix code problem is to determine, for a given list W=[w/sub 1/,...,w/sub n/] of n positive symbol weights, a list L=[l/sub 1/,...,l/sub n/] of n corresponding integer codeword lengths such that /spl Sigma//sub i=1//sup n/2/sup -li//spl les/1 and /spl Sigma//sub i=1//sup n/w/sub i/l/sub i/ is minimized. Let us consider the case where W is already sorted. In this case, the output list L can be represented by a list M=[m/sub 1/,...,m/sub H/], where m(l/sub 1/), for l=1,...,H, denotes the multiplicity of the codeword length l in L and H is the length of the greatest codeword. Fortunately, H is proved to be O(min{log(1/(p/sub 1/)),n}), where p/sub 1/ is the smallest symbol probability, given by w/sub 1///spl Sigma//sub i=1//sup n/w/sub i/. We present the F-LazyHuff and the E-LazyHuff algorithms. F-LazyHuff runs in O(n) time but requires O(min{H/sup 2/,n}) additional space. On the other hand, E-LazyHuff runs in O(nlog(n/H)) time, requiring only O(H) additional space. Finally, since our two algorithms have the advantage of not writing at the input buffer during the code calculation, we discuss some applications where this feature is very useful.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Real-time VBR rate control of MPEG video based upon lexicographic bit allocation Performance of quantizers on noisy channels using structured families of codes SICLIC: a simple inter-color lossless image coder Protein is incompressible Encoding time reduction in fractal image compression
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1