Sentence examples for sparsity knowledge from inspiring English sources

The proposed algorithm enables robust spectrum estimation without the priori sparsity knowledge, and keeps low computational complexity simultaneously, which is more suitable for practical on-line applications.

The functional groups in GSEA are drawn from different human-curated databases, which can have a number of limitations such as sparsity, knowledge lag-time, and limited vocabularies.

Although high-dimensional sparse models have been widely used in genetic association studies (Cantor et al. 2010; Engelhardt and Stephens 2010; Stegle et al. 2010; Parts et al. 2011; Zhou and Stephens 2012) to our knowledge, sparsity has not yet been applied to estimating a G-matrix.

The OMP algorithm requires the knowledge of sparsity beforehand.

In this scenario, we need to use the knowledge of sparsity in some way.

At the same time, the imposition of the sparsity constraint requires domain knowledge.

The essence of CS is to exploit prior knowledge of sparsity of the objective signal.

However, due to the prior knowledge of sparsity information, one can reconstruct x perfectly via properly designed reconstruction algorithms.

SS-SAMP does not require a priori knowledge of sparsity as in the case of other mentioned algorithms.

We remark that Algorithm 3, RFPI, LP, and GAMP do not require the knowledge of sparsity of original signals.

In order to incorporate the prior knowledge of sparsity when updating the corrector covariance, this section develops an EKF-based approach, which leads to enhanced tracking performance.