Sentence examples for maps are equivalent from inspiring English sources

"By using the definitions in the IUCN guidelines, it is clear that our range maps are equivalent to IUCN's Extent of Occurrence and not the Area of Occupancy," he said, adding that his team "remains convinced" of the superior accuracy of their method. .

Note that such signed (binary) lateralization maps are equivalent to the categorical laterality indices that are typically generated after thresholding the regional laterality indices (e.g. typically thersholded at 0.2 (Springer et al., 1999) or even at 0.5 as in (Cai et al., 2010; Van der Haegen et al., 2012)).

In this context, the fitting of two density maps is equivalent to finding an optimal correspondence index ϕ : i → j and a transformation that minimizes the wRMS (Supplementary Material for a detailed flowchart of the method).

To relate the topological properties of the normative connectome to meta-analytically derived grey matter lesions, we first assumed that the degree of a voxel in the meta-analytic lesion maps was equivalent to the degree of the regional node of the DTI network in which it was located.

For the rest of this section, read mapping and tag mapping are equivalent expressions.

The injectivity (one-to-one property) of rational Bézier curve as a mapping function is equivalent to the curve without self-intersections.

Such a map is equivalent to a POVM.

Therefore, it follows from Lemma 2.2 and (2.3) that the definition of a strongly successively pseudocontractive mapping is equivalent to the following definition.

The problem of finding a fixed point of a nonexpansive mapping is equivalent to the problem of finding a zero of the following operator equation: 0 ∈ A ( x ) (1.1).

Since for a nonexpansive mapping, the mapping is -inverse strongly monotone, the problem of finding an element of, where denotes the set of fixed points of the nonexpansive mapping, is equivalent to that of finding an element of, where denotes the set of solutions of the mapping, and contained in the class of problem (1.9).

Assuming uniform priors, for example, the mode of the posterior distribution (MAP) is equivalent to the ML estimator.