The phrase "a certain sparse" is not correct in written English.
It seems to be an incomplete or incorrect construction, as "sparse" typically requires a noun to modify.
Example: "The landscape was a certain sparse beauty that captivated the travelers."
Alternatives: "a particular sparse" or "an unusually sparse".
To restrict the redundant parameter adjustments, they proposed sparse MAP (SMAP) adaptation in which a typical MAP problem is maximized with certain sparse constraints.
CS theory asserts that, if a signal has a sparse representation in a certain space, one can use the random sampling to obtain the measurements and successfully reconstruct the signal with overwhelming probability by nonlinear algorithms, as stated in Section 'Signal model'.
CS allows to sense a signal in a low-dimensional form, however, for this purpose, the captured signal is required to be sparse in a certain domain[14, 15].
Compressive sensing (CS) enables reconstructing a signal that is sparse in a certain domain from its measurements obtained at a rate significantly lower than the Nyquist frequency[1].
The theory suggests that if the signal is sparse in a certain domain, it can be accurately reconstructed by a small amount sampling signal with high probability [3, 4].
We know that signals and natural images must be sparse in a certain transform domain or dictionary, in order for them to be reconstructed exactly within the CS framework.
The CS principle claims that if a signal is compressive or sparse in a certain transform domain, it can be projected onto a low-dimensional space using a measurement matrix which is irrelevant with transform basis while still enabling reconstruction at high probability from these small numbers of random linear measurements via solving an optimization problem.
If a signal is compressible in the sense that its representation in a certain linear canonical basis is sparse, it can then be recovered from measurements obtained at a rate much lower than the Nyquist frequency using the technique of compressive sensing (CS) [1 3].
Sparsity-based regularization methods for image restoration assume that the underlying image has a good sparse approximation under a certain system.
After a certain amount of turbulence, and blessedly sparse music, Gidget (Sandra Dee) and her boyfriend, Moondoggie (James Darren), do finally hang up their boards; even their slightly grizzled guru, a self-proclaimed "surf bum" called Kahuna (Cliff Robertson), takes a job in the end.
