Sentence examples for sparse methodology from inspiring English sources

Taking into account the sparse nature of impact-force in time domain, we develop a general sparse methodology based on minimizing l1-norm for solving the highly underdetermined model of impact-force reconstruction.

4, we extend sparse decoding methodology to spatio-temporal stimuli and functional identification of spatio-temporal complex cells.

The capacity of existing software packages to fit these complex models is largely due to the use of the sparse matrix methodology and the average information algorithm.

The capacity of existing software to fit these complex models to 'real' data sets, (see ASReml) is largely due to the use of sparse matrix methodology and the AI algorithm [ 13].

This program can also aid in the selection of sampling times for accurate calculation of AUC24h (diurnal area under the blood concentration time curve) using sparse-sampling methodologies (one, two or three samples).

An advantage of sparse signal representation methodology is that it has robustness to limited number of snapshots for DOA estimation [8].

Whilst there are numerous reviews and studies providing evidence that CIMT is strongly related to CVD incidents and that it is a well validated research tool, variations in methodology and sparse clinical data has prevented widespread adoption of this technique for routine assessment in clinical settings [ 74].

We utilize a methodology that augments sparse hydraulic information (hard data) with more widely available hydrogeologic information to generate equiprobable maps of hydrogeologic properties that incorporate patterns of connected permeable zones.

Unfortunately, the core orthology groups are small enough, and the interactions between and within them sparse enough, that the testing methodology precludes anything other than leave-one-out cross-validation (described in Section 3.8).

Rather than trying to use cutting-edge advanced meta-analysis methodology, in a sparse data context, it may often be wiser to restrict focus to simpler methods (e.g. fixed effect models) and be realistic about the potentially limited conclusions that can be drawn from the data.

To address the above problem, we adopted the matrix decomposition methodology "low-rank and sparse decomposition" (LRSDec) to decompose EMAP data matrix into low-rank part and sparse part.