Metrics for Symbol Clustering from a Pseudoergodic Information Source

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. Keywords. Metrics, information source, codification, entropy, genetic algorithm.

• Type: Conference
• Year: 2003
• Where: ENC
• Authors: Angel Fernando Kuri Morales, Oscar Herrera-Alcantara
• Keywords: ENC 2003, Genetic Algorithm, Information Source, Pseudoergodic Information Source