This paper provides a mathematical analysis of transform compression in its relationship to linear and nonlinear approximation theory. Contrasting linear and nonlinear approximatio...
Albert Cohen, Ingrid Daubechies, Onur G. Guleryuz,...
In this paper we investigate the usage of random ortho-projections in the compression of sparse feature vectors. The study is carried out by evaluating the compressed features in ...
The innate verbosity of the Extensible Markup Language remains one of its main weaknesses, especially when large XML documents are concerned. This problem can be solved with the a...
Przemyslaw Skibinski, Szymon Grabowski, Jakub Swac...
This paper considers a large-scale wireless sensor network where sensor readings are occasionally collected by a mobile sink, and sensor nodes are responsible for temporarily stori...
Compressive Sensing (CS) is an emerging area which uses a relatively small number of non-traditional samples in the form of randomized projections to reconstruct sparse or compres...
Ali Cafer Gurbuz, James H. McClellan, Volkan Cevhe...