Sentence examples for minimizing a metric from inspiring English sources

In additional, they usually estimate the motion error by minimizing a metric, which does not release the true movement, etc.

Given another spectrum q = q m : m = 1, 2, …, M, the goal is then to match peaks by minimizing a metric quantifying the quality of match between p and q.

This amounts to maximizing (or minimizing) a metric called the assortativity index of the edges that constitute the matching.

It is basically an optimization method that starts from an initial estimate of T and iteratively refines it by generating pairs of corresponding points on the scans and minimizing an error metric, e.g., the sum of squared distances between corresponding points.

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.

Different permutations of a simulated algorithm are applied to the problem of developing a systems architecture that minimizes a multicriterion metric (cost per image) for the NASA Origins Terrestrial Planet Finder mission.

This raises the problem of quantizer design optimized for distributed estimation systems where the goal is to design independently operating quantizers that minimize a global metric such as the estimation error (a function of all sensor readings).

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.

The objective is to control the movement of multiple cooperating agents allocated over these line segments in order to minimize an uncertainty metric associated with a finite set of data sources/targets.

For a given s 2 R, the best s 1 R that minimizes the decoding metric can alternatively be found by minimizing a quadratic function of s 1 R given on the right-hand side of (20).