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Metrics for Symbol Clustering from a Pseudoergodic Information Source
Tlaxcala, Mexico September 08-September 12
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ENC.2003.1232912Fourth Mexican International Conferen ...
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Angel Fernando Kuri-Morales, Instituto Aut?nomo de M?xico
Oscar Herrera-Alc?ntara, Centro de Investigaci?n en Computaci?
We discuss a set of metrics, which aims to facilitate the formation of symbol groups from a pseudoergodic information source. An optimal codification can then be applied on the symbols(such as Huffman Codes [1]) for zero memory sources where it tends to the theorical limit of compression limited by the entropy. These metrics can be used as a fitness measure of the individuals in the Vasconcelos genetic algorithm as an alternative to exhaustive search.
Index Terms:
Metrics, information source, codification, entropy, genetic algorithm
Citation:
Angel Fernando Kuri-Morales, Oscar Herrera-Alc?ntara, "Metrics for Symbol Clustering from a Pseudoergodic Information Source," enc, pp.330, Fourth Mexican International Conference on Computer Science, 2003
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