Fourth Mexican International Conference on Computer Science
Metrics for Symbol Clustering from a Pseudoergodic Information Source
Tlaxcala, Mexico
September 08-September 12
ISBN: 0-7695-1915-6
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