We address the problem of signal compression, basing on the mathematical model, in which a set of all possible signals is considered as a function space with a metric . The main a...
Scalar quantization is the most practical and straightforward approach to signal quantization. However, it has been shown that scalar quantization of oversampled or Compressively ...
It is known that modeling an information source via a symbolic dynamical system evolving over the unit interval, leads to a natural lossless compression scheme attaining the entro...
The new eSBR tool of MPEG-D Universal Speech and Audio Coding offers a great advantage in compression of high frequency content, however it produces audible artifacts for sounds w...
Tomasz Zernicki, Maciej Bartkowiak, Marek Domanski
In this paper, we propose a bilevel sparse coding model for coupled feature spaces, where we aim to learn dictionaries for sparse modeling in both spaces while enforcing some desi...