Sentence examples for by considering a sparse from inspiring English sources

The coding gain is achieved by considering a sparse representation for the excitation source.

With increasing number of metabolic species within the pathway, the derivative process approach might become computationally costly due to the inference of a large number of hyper-parameters and a matrix inversion step; however, this limitation potentially might be addressed by considering a sparse approximation for the full covariance matrix of all metabolic species (Alvarez and Lawrence, 2009).

This paper focuses on parallel algorithms for matrix assembly and matrix rearrangement related to FEM procedures by considering a sparse-matrix storage format.

In this paper, the three above-mentioned procedures, i.e., assembling the stiffness matrix, solving linear equations, and rearranging the stiffness matrix, are implemented by considering a sparse-matrix storage format ("Implementation and GPU parallelization").

Also when considering an sparse data set P (M | D ) is diffuse, meaning that P (M | D ) will not be properly represented by a single structure M *.

We consider a sparse wideband spectrum contains 10 TV bands each with 6-MHz bandwidth.

Concluding remarks are presented in Section 5. Consider a sparse multipath communication system, as shown in Figure 2. Figure 2 A typical sparse multipath communication system.

Besides this approach, Gao et al. [66] explore another sparse coding-based approach (LScSPM) by considering the instable sparse code produced by different sparse coding techniques [60, 62].

We also evaluate the performance of an OXC equipped with an FDL bank for both the SPL and SPC scenarios by considering sparse wavelength converters (limited number of full range wavelength converters).

To deal with the aforementioned problems, this paper studies the robust design of the FSBB with sparse tap weights via convex optimization by considering some a priori knowledge of microphone mismatches.

In the first example, we consider a typical sparse signal recovery problem.