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103
Voted
ICASSP
2008
IEEE
15 years 8 months ago
Model-based sparsity projection pursuit for lattice vector quantization
In this work we present an efficient coding scheme suitable for lossy image compression using a lattice vector quantizer (LVQ) based on statistically independent data projections...
Leonardo H. Fonteles, Marc Antonini, Ronald Phlypo
ICC
2007
IEEE
245views Communications» more  ICC 2007»
15 years 8 months ago
Low Complexity MMSE Vector Precoding Using Lattice Reduction for MIMO Systems
—In this paper, a lattice-reduction-aided (LRA) With such an approximation, the complexity of VP is greatly minimum mean square error (MMSE) vector precoding (VP) is reduced. pro...
Feng Liu, Ling-ge Jiang, Chen He
125
Voted
FOCS
2004
IEEE
15 years 5 months ago
Hardness of Approximating the Shortest Vector Problem in Lattices
Let p > 1 be any fixed real. We show that assuming NP RP, there is no polynomial time algorithm that approximates the Shortest Vector Problem (SVP) in p norm within a constant ...
Subhash Khot
101
Voted
FOCS
1998
IEEE
15 years 6 months ago
The Shortest Vector in a Lattice is Hard to Approximate to Within Some Constant
We show that approximating the shortest vector problem (in any p norm) to within any constant factor less than p 2 is hard for NP under reverse unfaithful random reductions with i...
Daniele Micciancio
DCC
2006
IEEE
16 years 1 months ago
Optimal Index Assignment for Multiple Description Lattice Vector Quantization
Optimal index assignment of multiple description lattice vector quantizer (MDLVQ) can be posed as a large-scale linear assignment problem. But is this expensive algorithmic approa...
Xiang Huang, Xiaolin Wu