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Information Theory in Scientific Visualization
AbstractIn recent years, there is an emerging direction that leverages information theory to solve many challenging problems in scientific data analysis and visualization. In this article, we review the key concepts in information theory, discuss how the principles of information theory can be useful for visualization, and provide specific examples to draw connections between data communication and data visualization in terms of how information can be measured quantitatively. As the amount of digital data available to us increases at an astounding speed, the goal of this article is to introduce the interested readers to this new direction of data analysis research, and to inspire them to identify new applications and seek solutions using information theory.
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Wang, C.; Shen, H.-W. Information Theory in Scientific Visualization. Entropy 2011, 13, 254-273.View more citation formats
Wang C, Shen H-W. Information Theory in Scientific Visualization. Entropy. 2011; 13(1):254-273.Chicago/Turabian Style
Wang, Chaoli; Shen, Han-Wei. 2011. "Information Theory in Scientific Visualization." Entropy 13, no. 1: 254-273.
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