Sentence examples for sparse process from inspiring English sources

The use of modelling opens up great opportunities for making maximum use of sparse process data, for optimum co-selection of material and process, and for providing the designer with feedback on the likely influence of processing on the viability and cost of a design as well as indicating trial processing parameters.

(4) The data of these nearest neighbors would be sparse processed.

Additionally, sparse processes are also visible extending into the MoXII from both the fastigial and dentate tracing by the Allen Institute.

It is important to note that we were not able to reproducibly visualize neurons with elaborate arbors over multiple neuropils and only diffuse and sparse processes in the MB lobes, such as octopaminergic neurons and SIFamide peptidergic neurons (data not shown).

The number of basis functions is adaptively determined by minimizing the number of nonzero components in the coefficient vector during the sparse regularization process.

The velocity model, which represents the relationship between true vehicle velocity and input command, is learned with an on-line sparse Gaussian process (GP).

This reduced-space boundary value problem (BVP) approach allows an efficient and robust solution of multistage optimal control and design optimization problems for large, sparse DAE process models of index one.

Given that dynamic texture and statistical noise are typically distributed through the entire space anisotropically, their influence on an actual signal will be obviously weakened after application of the sparse projection process.

From the results got from Figures 17 and 18, we conclude that in the nested sparse sampling process, besides its advantage of less samplers, with N1 and N2 chosen larger, the bandwidth of the PSD occupied will becomes narrower, which increases the spectrum efficiency.

We extended a previously proposed signal separation algorithm (SSA) to process sparse four-dimensional NMR data.

For sparse graphs, this process has an upper complexity bound of (mathcal{O} mcdot log(m cdot s_{C}^{max})), where (s_{C}^{max}) is the maximum number of neighbour communities that a community may have at any time of the process.