Your English writing platform
Discover LudwigSuggestions(5)
Exact(43)
Vanishing moments of the basis functions permit a sparse representation of the solution and operators.
Finding such a sparse representation of a signal involves solving an optimization problem.
We presented a novel method to obtain a sparse representation of multiview images.
The method uses non-aliasing sontourlet transform as a sparse representation of CT image.
This article presents a novel method to obtain a sparse representation of multiview images.
This was a vector of 512 features, which could be considered as a sparse representation of the image patch's appearance.
Similar(17)
Masking is a common approach in speech separation given latent states, that is often implemented in the STFT domain, which provides a sparse representations of speech signals.
NSST, as a multi-scale directional representation, is able to give a good sparse representation of an image.
The problem of finding a sparse representation which uses the minimum number of blocks of D is given as the following optimization problem begin{array}{*{20}l} & text{minimize} quad sum_{i=0}^{d-1} Ileft |tilde{mathbf{h}}[!i]|_{q}right) & text{subject to} quad {tilde{mathbf{y}}}=mathbf{D}{tilde{mathbf{h}}}, end{array} (12).
A sparse representation is a decomposition of a signal on a very small set of components of an over-complete basis (called dictionary) which is adapted to the processed data.
At each frame, only those spectral peaks with an amplitude higher than a threshold μ are selected, removing the rest of spectral information and obtaining this way a sparse representation containing a subset of spectral bins.
More suggestions(2)
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com