Sciweavers

Free Online Productivity Tools i2Speak i2Symbol i2OCR iTex2Img iWeb2Print iWeb2Shot i2Type iPdf2Split iPdf2Merge i2Bopomofo i2Arabic i2Style i2Image i2PDF iLatex2Rtf Sci2ools

14

ENC
2003
IEEE

favoriteEmaildiscussreport

107views Theoretical Computer Science» more ENC 2003»

Metrics for Symbol Clustering from a Pseudoergodic Information Source

13 years 10 months ago

Metrics for Symbol Clustering from a Pseudoergodic Information Source

Download cursos.itam.mx

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.

Angel Fernando Kuri Morales, Oscar Herrera-Alcanta

Real-time Traffic

ENC 2003 | Genetic Algorithm | Information Source | Pseudoergodic Information Source |

claim paper

Related Content

» Efficient Compression from Nonergodic Sources with Genetic Algorithms

» Reinforcement Learning Task Clustering

» Cluster Generation and Labeling for Web Snippets A Fast Accurate Hierarchical Solution

» Efficient concept clustering for ontology learning using an event life cycle on the web

» Integrated KL Kmeans Laplacian Clustering A New Clustering Approach by Combining Attribut...

» Assessing the functional coherence of modules found in multipleevidence networks from Arab...

» Densitybased clustering using graphics processors

» A Selective Cluster Index Scheduling Method in OFDMA

» Clustering Appearance for Scene Analysis

Post Info
More Details (n/a)

Added	04 Jul 2010
Updated	04 Jul 2010
Type	Conference
Year	2003
Where	ENC
Authors	Angel Fernando Kuri Morales, Oscar Herrera-Alcantara

Comments (0)