Abstract
A new data structure is investigated, which allows fast decoding of texts encoded by canonical Huffman codes. The storage requirements axe much lower than for conventional Huffman trees, O(log2 n) for trees of depth O(log n), and decoding is faster, because a part of the bit-comparisons necessary for the decoding may be saved. Empirical results on large real-life distributions show a reduction of up to 50% and more in the number of bit operations.
Cite
CITATION STYLE
Klein, S. T. (1997). Space- and time-efficient decoding with canonical huffman trees: Extended abstract. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1264, pp. 65–75). Springer Verlag. https://doi.org/10.1007/3-540-63220-4_50
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