Sentence examples for matrix decomposition model from inspiring English sources

A recently developed low-rank (L) plus sparse (S) matrix decomposition model (L+S) is one of the methods that has been introduced to reconstruct images from undersampled dynamic MRI data.

In this paper, we study on the baseline problem of the traffic matrix satisfying a refined traffic matrix decomposition model, since this model extends the assumption of the baseline traffic component to characterize its smoothness, and is more realistic than the existing traffic matrix models.

The algorithm is based on a two-stage constrained matrix decomposition model.

The method is based on a two-stage constrained matrix decomposition model.

The NCA method and a two-stage matrix decomposition model in [ 28] assume that the connectivity matrix is fully known, and, therefore, it does not predict any new interaction among the genes and transcription factors.

It would be interesting in future work to incorporate matrix decomposition models that explicitly incorporate different noise models (e.g., noisy ICA [28]) for a more robust un-mixing of material responses from instrumental responses.

Related matrix decomposition models and iterative, dependence-seeking projections have been suggested based on generalized singular value decomposition [ 3] and independent component analysis [ 35].

Compared with NHML, PROCOV has numerous new features, including, for instance, a command-line argument for setting models, parameters, input and output data; implementing protein models and four covarion models (NHML only implements the Galtier model for DNA data); new functions for matrix decomposition, matrix operations and computing derivatives.

Our generic data transformation procedure is built on a decomposition model for the double-mutant fitness matrix.

We recently developed a two-stage matrix decomposition method that combine the characteristics of projection and model-based approaches for the discovery of transcriptional modules (Li et al., 2007).

We then turn to stochastic finite-time controller analysis and design to guarantee that the stochastic model is stochastically H∞ finite-time bounded by employing matrix decomposition method.