{"title":"文本文件无损数据压缩中涉及字母编码和有限长度编码的备选算法","authors":"R. Radescu","doi":"10.1109/ISFEE.2016.7803154","DOIUrl":null,"url":null,"abstract":"Coding algorithms are generally aimed at minimizing the output code length encoding speed once the code has been designed. Moreover, most codes use a binary alphabet. This paper examines other issues related to coding, such as additional constraints imposed on the channel. Code generation will be considered where there is a limit on code words. Limits the application of such systems is a practical example of data compression where fast decoding is essential. When all code words correspond to a single word in memory (usually 32 bits, but there are situations that take 64-bit) can be used canonical decoding. If the deadline cannot be guaranteed, however, required the use of slower decoding methods. This paper also deals with the alphabetic code generation, where lexicographic arrangement of words by their code symbols must correspond to the original order in which the symbols were taken coding system. When an alphabetic code is used to compress a database that can be sorted in the same, order they would have had if the database records were first decompressed and then sorted. It also corresponds to alphabetic code trees binary search trees, which have applications in a wide variety of search problems. Assumption that the symbols are sorted by probability is not suitable for this scenario. The problem of finding codes for non-binary alphabets channel will be examined in detail. The subsequent experimental results cover the problem of alphabetic coding and of limited length coding.","PeriodicalId":240170,"journal":{"name":"2016 International Symposium on Fundamentals of Electrical Engineering (ISFEE)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Alternative algorithms involving alphabetical coding and limited length encoding in lossless data compression of text files\",\"authors\":\"R. Radescu\",\"doi\":\"10.1109/ISFEE.2016.7803154\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Coding algorithms are generally aimed at minimizing the output code length encoding speed once the code has been designed. Moreover, most codes use a binary alphabet. This paper examines other issues related to coding, such as additional constraints imposed on the channel. Code generation will be considered where there is a limit on code words. Limits the application of such systems is a practical example of data compression where fast decoding is essential. When all code words correspond to a single word in memory (usually 32 bits, but there are situations that take 64-bit) can be used canonical decoding. If the deadline cannot be guaranteed, however, required the use of slower decoding methods. This paper also deals with the alphabetic code generation, where lexicographic arrangement of words by their code symbols must correspond to the original order in which the symbols were taken coding system. When an alphabetic code is used to compress a database that can be sorted in the same, order they would have had if the database records were first decompressed and then sorted. It also corresponds to alphabetic code trees binary search trees, which have applications in a wide variety of search problems. Assumption that the symbols are sorted by probability is not suitable for this scenario. The problem of finding codes for non-binary alphabets channel will be examined in detail. The subsequent experimental results cover the problem of alphabetic coding and of limited length coding.\",\"PeriodicalId\":240170,\"journal\":{\"name\":\"2016 International Symposium on Fundamentals of Electrical Engineering (ISFEE)\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 International Symposium on Fundamentals of Electrical Engineering (ISFEE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISFEE.2016.7803154\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Symposium on Fundamentals of Electrical Engineering (ISFEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISFEE.2016.7803154","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Alternative algorithms involving alphabetical coding and limited length encoding in lossless data compression of text files
Coding algorithms are generally aimed at minimizing the output code length encoding speed once the code has been designed. Moreover, most codes use a binary alphabet. This paper examines other issues related to coding, such as additional constraints imposed on the channel. Code generation will be considered where there is a limit on code words. Limits the application of such systems is a practical example of data compression where fast decoding is essential. When all code words correspond to a single word in memory (usually 32 bits, but there are situations that take 64-bit) can be used canonical decoding. If the deadline cannot be guaranteed, however, required the use of slower decoding methods. This paper also deals with the alphabetic code generation, where lexicographic arrangement of words by their code symbols must correspond to the original order in which the symbols were taken coding system. When an alphabetic code is used to compress a database that can be sorted in the same, order they would have had if the database records were first decompressed and then sorted. It also corresponds to alphabetic code trees binary search trees, which have applications in a wide variety of search problems. Assumption that the symbols are sorted by probability is not suitable for this scenario. The problem of finding codes for non-binary alphabets channel will be examined in detail. The subsequent experimental results cover the problem of alphabetic coding and of limited length coding.