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» Iterative compression and exact algorithms
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ICIP
1998
IEEE
14 years 11 months ago
Reducing the Computational Complexity of a Map Post-Processing Algorithm for Video Sequences
Maximum a posteriori (MAP) filtering using the HuberMarkov random field (HMRF) image model has been shown in the past to be an effective method of reducing compression artifacts i...
Mark A. Robertson, Robert L. Stevenson
ICASSP
2011
IEEE
13 years 1 months ago
A hybrid compressed sensing algorithm for sparse channel estimation in MIMO OFDM systems
Due to multipath delay spread and relatively high sampling rate in OFDM systems, the channel estimation is formulated as a sparse recovery problem, where a hybrid compressed sensi...
Chenhao Qi, Lenan Wu
CORR
2010
Springer
165views Education» more  CORR 2010»
13 years 10 months ago
Compressed Sensing for Sparse Underwater Channel Estimation: Some Practical Considerations
We examine the use of a structured thresholding algorithm for sparse underwater channel estimation using compressed sensing. This method shows some improvements over standard algo...
Sushil Subramanian
ISCC
2000
IEEE
104views Communications» more  ISCC 2000»
14 years 2 months ago
Dynamic Routing and Wavelength Assignment Using First Policy Iteration
With standard assumptions the routing and wavelength assignment problem (RWA) can be viewed as a Markov Decision Process (MDP). The problem, however, defies an exact solution bec...
Esa Hyytiä, Jorma T. Virtamo
DAM
2010
105views more  DAM 2010»
13 years 7 months ago
An iterative approach to graph irregularity strength
An assignment of positive integer weights to the edges of a simple graph G is called irregular if the weighted degrees of the vertices are all different. The irregularity strength,...
Michael Ferrara, Ronald J. Gould, Michal Karonski,...