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On the Memory Efficiency and Search time for Huffman Coding Scheme

机译:关于霍夫曼编码方案的记忆效率和搜索时间

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Hashemian has proposed a technique to improve the memory efficiency and the symbol search time of the Huffman compression coding scheme. This is achieved by uniform partitioning and clustering of the single-side growing Huffman tree (SGH-tree). In the example given by Hashemian for a 32-symbol source with 13-level SGH-tree, the memory requirement is 126 words and the memory efficiency is only 50%, compared to 2 and 0.39%, respectively, for unstructured memory environment La this paper, the memory efficiency and the search time are further improved by extending the set of decoded symbols; the new added symbols are groups of consecutive single symbols with certain criterion. The extended set of decoded symbols keeps the same structure of the SGH-tree; thus, there is no increase in the memory requirement It is required to modify the decoding procedure, resulting in a change of the contents of the look up tables (LUTs) of the clusters, the super table (ST) of the SGH-tree, and the memory (RAM) table. With this technique, the memory requirement is 120 words and the memory efficiency is 82%. Since the new added symbols are groups of consecutive single symbols, the search time for some symbols is reduced, leading to an improvement in the search time for modified technique.
机译:Hashemian提出了一种提高存储器效率和霍夫曼压缩编码方案的符号搜索时间的技术。这是通过均匀的分区和单侧生长霍夫曼树(SGH树)的聚类来实现的。在具有13级SGH树的32符号源给出的哈希姆给出的示例中,内存要求是126个单词,内存效率仅为50%,分别为2%和0.39%,对于非结构化的存储器环境LA通过扩展一组解码的符号,进一步提高了纸张,内存效率和搜索时间;新添加的符号是具有某些标准的连续单个符号组。扩展的一组解码符号保持了SGH树的相同结构;因此,内存要求没有增加,需要修改解码过程,从而导致群集的查找表(LUT)的内容的变化,SPRO-TRE的超级表(ST),和记忆(RAM)表。利用这种技术,内存要求是120字,内存效率为82%。由于新添加的符号是连续单个符号的组,因此减少了一些符号的搜索时间,从而导致修改技术的搜索时间的改进。

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