最小方差霍夫曼编码设计及应用研究  

Research on Design and Application of Minimum Variance Huffman Coding

作　　者：王梦梵 李晓毅 冯克涛 朱刚[3] 王邠 WANG Mengfan;LI Xiaoyi;FENG Ketao;ZHU Gang;WANG Bin(School of Computer and Information Science,Chongqing Normal University,Chongqing 401331,China;Communication Sergeant School,The Army Engineering University of PLA,Chongqing 400035,China;Unit 31306 of PLA,Chengdu 610036,China)

机构地区：[1]重庆师范大学计算机与信息科学学院,重庆401331 [2]陆军工程大学通信士官学校,重庆400035 [3]中国人民解放军31306部队,四川成都610036

出　　处：《现代信息科技》2024年第9期87-90,96,共5页Modern Information Technology

摘　　要：随着云存储和云计算的发展,大量数据被上传及存储在服务器端。针对传统霍夫曼编码设计存在码字长度分布不均匀、码方差偏大、“字符—概率—码字”唯一对应难,引起储存空间占用大、解码误码率高的问题,文章基于“极小量扰动”思想提出一种最小方差霍夫曼编码设计方法。仿真结果表明,该文设计的最小方差霍夫曼编码码字长度分布更均匀,码方差更小,且所得编码能与符号对应;进行文本压缩实验时,压缩率分别为69.6%、65.9%、49.3%,能有效提升编码质量,降低冗余度。With the development of cloud storage and cloud computing,a large amount of data is uploaded and stored on the server side.In response to the problems of uneven codeword length distribution,large code variance,and difficulty in unique correspondence between characters,probabilities,and codewords in traditional Huffman coding design,which lead to large storage space occupation and high decoding error rate,this paper proposes a minimum variance Huffman coding design method based on the concept of“minimal disturbance”.The simulation results show that the minimum variance Huffman coding designed in this paper has a more uniform codeword length distribution,smaller code variance,and the obtained code can correspond to the symbols.When conducting text compression experiments,the compression rates are 69.6%,65.9%,and 49.3%,respectively,which can effectively improve coding quality and reduce redundancy.

关 键 词：云存储 霍夫曼编码 最小方差 数据压缩 

分 类 号：TN911.21[电子电信—通信与信息系统]