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» Dimensional behaviour of entropy and information
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TIT
1998
102views more  TIT 1998»
13 years 5 months ago
On Characterization of Entropy Function via Information Inequalities
—Given n discrete random variables = fX1;111; Xng, associated with any subset of f1; 2; 111; ng, there is a joint entropy H(X ) where X = fXi:i 2 g. This can be viewed as a f...
Zhen Zhang, Raymond W. Yeung
APVIS
2011
12 years 5 months ago
View point evaluation and streamline filtering for flow visualization
Visualization of flow fields with geometric primitives is often challenging due to occlusion that is inevitably introduced by 3D streamlines. In this paper, we present a novel v...
Teng-Yok Lee, Oleg Mishchenko, Han-Wei Shen, Roger...
UC
2010
Springer
13 years 3 months ago
Characterising Enzymes for Information Processing: Towards an Artificial Experimenter
The information processing capabilities of many proteins are currently unexplored. The complexities and high dimensional parameter spaces make their investigation impractical. Diff...
Chris Lovell, Gareth Jones, Steve R. Gunn, Klaus-P...
CORR
2006
Springer
99views Education» more  CORR 2006»
13 years 5 months ago
A New Approach for Capacity Analysis of Large Dimensional Multi-Antenna Channels
This paper adresses the behaviour of the mutual information of correlated MIMO Rayleigh channels when the numbers of transmit and receive antennas converge to + at the same rate. ...
Walid Hachem, Oleksiy Khorunzhiy, Philippe Loubato...
MMMACNS
2005
Springer
13 years 11 months ago
Networks, Markov Lie Monoids, and Generalized Entropy
The continuous general linear group in n dimensions can be decomposed into two Lie groups: (1) an n(n-1) dimensional ‘Markov type’ Lie group that is defined by preserving the ...
Joseph E. Johnson