Sentence examples for sparsity characteristics from inspiring English sources

Additionally, large numbers of parameters need to be estimated, and due to the sparsity characteristics of natural language, the probability of low- and zero-frequency events is estimated crudely and inaccurately using various smoothing algorithms.

As in the double source experiment, WISTA still obtained the best performance because it could maintain its preferable sparsity characteristics.

Considering the source sparsity characteristics and the insufficiency of the measured data, the l1-norm penalty term has been adopted in the regularization method and was successfully applied to BLT [ 24– 26, 33].

Consistent with our anticipation, the reconstruction results became better as the PSR decreased, especially for the l2 regularization methods (TTLS, Tikhonov), which could be mainly attributed to the fact that the weight matrix was overdetermined and the sparsity characteristics of the inverse problem didn't pan out.

Such a block sparsity characteristic, embodied by inner-clusters MPCs, can be properly employed to further design a more efficient channel estimation algorithm with a much lower complexity.

The sparsity is a typical characteristic of the transform domain where noise is uniformly spread throughout all coefficients, and the data is represented by a small subset of big coefficients [38].

To create this framework, an experimental design applies several CF configurations, which are characterized by different data-reduction techniques, CF methods, and similarity measures, to binary purchase data sets with distinct input data characteristics, i.e., sparsity level, purchase distribution, and item user ratio.

This is expected because IGMRF and sparsity priors together capture the disparity characteristics in different ways and their combination serves as a better regularizer.

It proves superior performance for a set of system graphs featuring specific properties found in human-made task graphs, since it exploits their typical characteristics such as locality, sparsity, and their degree of parallelism.

In the control group, corresponding place field characteristics, including spatial information sparsity and place field size, remained stable across 6 recording sessions.

These characteristics are attributed to the sparsity constraint greatly amplifying the original heterogeneity.