Compressing massive geophysical datasets using vector quantization

Journal of Computational and Graphical Statistics

Volumn 11, Issue 1, 2002, Pages 44-62

  Braverman, Amy ^a  

^a CALIFORNIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Clustering; ECVQ algorithm; K means algorithm; Monte Carlo methods; Self consistency

Indexed keywords

EID: 0036004138     PISSN: 10618600     EISSN: None     Source Type: Journal    
DOI: 10.1198/106186002317375613     Document Type: Article

References (14)

1. Refining initial points for K-means clustering
2. Entropy-constrained vector quantization
3. Squashing flat files flatter
4. What shall we do with the data we are expecting from upcoming earth observation satellites?
5. Statistical, physical, and computational aspects of massive data analysis and assimilation in atmospheric applications
6. Some methods for classification and analysis of multivariate observations
7. Efficient and effective clustering methods for spatial data mining
8. Self-consistency: A fundamental concept in statistics