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» Polar codes are optimal for lossy source coding
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JSA
2007
84views more  JSA 2007»
13 years 7 months ago
Optimizing data structures at the modeling level in embedded multimedia
Traditional design techniques for embedded systems apply transformations on the source code to optimize hardwarerelated cost factors. Unfortunately, such transformations cannot ad...
Marijn Temmerman, Edgar G. Daylight, Francky Catth...
SAC
2009
ACM
14 years 2 months ago
GTfold: a scalable multicore code for RNA secondary structure prediction
The prediction of the correct secondary structures of large RNAs is one of the unsolved challenges of computational molecular biology. Among the major obstacles is the fact that a...
Amrita Mathuriya, David A. Bader, Christine E. Hei...
ASPDAC
2000
ACM
97views Hardware» more  ASPDAC 2000»
14 years 3 days ago
Symbolic debugging of globally optimized behavioral specifications
Symbolic debuggers are system development tools that can accelerate the validation speed of behavioral specifications by allowing a user to interact with an executing code at the ...
Inki Hong, Darko Kirovski, Miodrag Potkonjak, Mari...
CGO
2009
IEEE
14 years 2 months ago
OptiScope: Performance Accountability for Optimizing Compilers
Compilers employ many aggressive code transformations to achieve highly optimized code. However, because of complex target architectures and unpredictable optimization interaction...
Tipp Moseley, Dirk Grunwald, Ramesh Peri
ICIP
1995
IEEE
14 years 9 months ago
A lattice vector quantizer for generalized Gaussian sources
A fixed-rate lattice vector quantizer for generalized Gaussian (GG) sources is presented. By using the contour of counstant probability of a generalized Gaussian source to bound t...
Feng Chen, Zheng Gao, John D. Villasenor