Sentence examples for new normalization from inspiring English sources

To simplify the computation of eigensensitivity, a new normalization of the general nonlinear eigenproblem is presented.

In this regard, we employ interval arithmetic and introduce a new normalization technique based on interval distance of interval numbers.

The new normalization of the general eigenproblem derived here can degenerate to the familiar mass orthogonal relationship of undamped eigenvectors.

With the new normalization, the simulated flux is correctly set at the measured flux of 1.e-12 ergs cm-2 s-1.

By introducing an additional and new normalization condition, we construct two extended systems of linear equations with nonsingular coefficient matrices which are transpose to each other.

In response to this perceived gap, the development of a new normalization technique is considered in this paper that provides an extension of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method and objective weighting in materials selection.

Far more normalization techniques than the ones analyzed here exist (e.g. [ 39, 33, 1, 40]); most of the newer normalization techniques are non-linear as this is assumed to perform generally better than linear techniques.

Our method employs a new global normalization method (nonparametric empirical Bayes correction normalization) [ 14- 17], utilizes pre-defined enriched regions identified from single-sample enriched regions identification programs, uses statistical methods to define differential enriched regions, then defines binding pattern information for those differential enriched regions.

Our method employs a new global normalization method: nonparametric empirical Bayes (NEB) correction normalization, utilizes pre-defined enriched regions identified from single-sample peak calling programs, uses statistical methods to define differential enriched regions, then defines binding (histone modification) pattern information for those differential enriched regions.

This paper presents a new spatial normalization with affine transformation.

For example, when explaining a new weather normalization feature for their software that allows customers to see if facilities are using energy effectively no matter the weather, Bassa relied on graphs to share huge data sets with clients.