Sentence examples for implementing an approximation from inspiring English sources

We also provide a method for implementing an approximation of the regularized inversion of a SV-matrix, under the assumption of having smoothly spatially varying kernels, and enough regularization.

We also have proposed a method for implementing an approximation of the filtering of a SV-matrix regularized inverted, under the assumption of having smoothly varying kernels, and enough regularization.

A local adaptation of the sensitivity of the photoreceptors to an average illumination level can also be seen as implementing an approximation of a logarithmic transformation, provided that both the baseline and the sensitivity regarding deviations from the baseline are adapted in a corresponding manner.

In many real cases, there is a substantial amount of overlapping among the kernels with different deformations, so one can use a J ≪ R. Now we try to use the technique of deformable filtering to efficiently implement an approximation of the transposed SV-filtering, which is made by using the local PSFs as local IKs (see Section 2.1).

Improvements on this theory could be obtained by implementing: A) a better approximation for the Green's function describing the fluence at the fluorophore site, which could be obtained by using high-order solutions of the perturbation theory [ 26, 27, 42] or exact RTE solutions [ 39]; B) the whole integral on the volume V′.

The proposed model aims at designing and implementing a fast approximation algorithm that generates a feasible solution.

The second proposed model is a discrete one, which, despite implementing a discrete approximation of the system behaviour, allows to study more general conditions, such as series of partial charging/discharging operations.

We implement an iterative approximation procedure based on this idea, and the procedure demonstrates the desirable anytime property in experiments.

Video systems depart from this principle and implement an engineering approximation.

VBSSM implements an analytical approximation scheme to Bayesian state-space models and, unlike other related methods, does not take prior information (i.e. the seed network) into account for network reconstruction [ 84], such that networks were solely constructed from the experimental data.

Lin and Speed (1996) have implemented a numerical approximation to these matrices.