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» Sampling and Reconstruction of Operators
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JSAT
2008
85views more  JSAT 2008»
13 years 7 months ago
Parallel SAT Solving using Bit-level Operations
We show how to exploit the 32/64 bit architecture of modern computers to accelerate some of the algorithms used in satisfiability solving by modifying assignments to variables in ...
Marijn Heule, Hans van Maaren
ICASSP
2008
IEEE
14 years 2 months ago
Compressed sensing with sequential observations
Compressed sensing allows perfect recovery of sparse signals (or signals sparse in some basis) using only a small number of measurements. The results in the literature have focuse...
Dmitry M. Malioutov, Sujay Sanghavi, Alan S. Wills...
IJCNN
2000
IEEE
14 years 5 days ago
Improved Rotational Invariance for Statistical Inverse in Electrical Impedance Tomography
In this paper we show that rotational invariance can be improved in a neural network based EIT reconstruction approach by a suitably chosen permutation of the input data. The inpu...
Jani Lahtinen, Tomas Martinsen, Jouko Lampinen
JMM2
2008
80views more  JMM2 2008»
13 years 7 months ago
Reliable Transmission of Audio Streams in Lossy Channels Using Application Level Data Hiding
The paper improves the reliability of audio streams in a lossy channel. The mechanism groups audio data samples into source and carrier sets. The carrier set carry the information ...
Parag Agarwal, Balakrishnan Prabhakaran
JC
2007
119views more  JC 2007»
13 years 7 months ago
Deterministic constructions of compressed sensing matrices
Compressed sensing is a new area of signal processing. Its goal is to minimize the number of samples that need to be taken from a signal for faithful reconstruction. The performan...
Ronald A. DeVore