Sentence examples for minimizing a distance from inspiring English sources

Any image coming from the test set and characterized by vector x is classified by minimizing a distance.

It is shown that a simplified version of the above closed loop controls, that avoids linearization step for nonlinear systems, can be deduced by minimizing a distance measure similar to what has been done for arriving at open loop controls.

A straightforward way to approximate a scaled impulse vector α δ u using only inactive users is obtained by minimizing a distance between vectors α δ u and d u (32).

The paper describes the improvement of the reconstruction when a least-square fit algorithm, which minimizes a distance functional, is applied.

Once the search space (x in {mathbf {T}}) is constructed, our next goal is to find anchoring points P and Q (as shown by Fig. 2) which minimize a distance metric.

As in previous works, this problem is here faced by hybridizing a standard mathematical modeling approach with a new data-driven solver accounting for the phenomenological part of the problem, with the aim of finding a solution point, satisfying some constraints, that minimizes a distance to a given data-set.

On the other hand, existing algorithms for edge bundling have a different scope: network bundles aim at rendering aesthetically pleasing and topologically compact drawings; yet, the existing algorithms do not necessarily aim at minimizing a global distance metric.

By observing these figures, it is possible to confirm the following facts: Regardless of the configuration of the polygonal maps and the structure of bipartite graphs, it is possible to converge to the bundled routes minimizing a global distance metric within 1000 function evaluations and 15 independent runs.

Firstly, the identifiability of three piezoviscosity models (Barus, Roelands and WLF) is analyzed by minimizing a least squares distance between pressure viscosity responses.

We propose to minimize a composite distance that consists of two terms: a distance itself and a smoothness term.

The matrix Q that minimizes a given distance metric d ( R, R ̃ ) or that maximizes a given similarity metric s ( R, R ̃ ) is determined.