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 ...
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...
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...
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 ...
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...