Sentence examples for estimation of a given from inspiring English sources
In this work, we focus on the dynamic power consumption estimation of a given CiM implementation.
Another important parameter required is the depth estimation of a given object in the scene.
Numerical experiments, in this research, are carried out using simple database that are successfully applied by Ben-Akiva and Lermans [5] for model parameter estimation of a given model specification.
There are many density estimation methods including k-nearest-neighbour methods, histogram methods and kernel methods, which are localized with only a small proportion of all points which contribute most to the density estimation of a given point [18].
Our analyses allowed us to identify the most accurate set of statistics to be used for the estimation of a given parameter and indicated that no general rule can be proposed to select a specific combination of summary statistics – the set of summary statistics providing the best accuracy varies depending on the parameter to be estimated.
To begin with, they measured the entropy estimations of a given executable and change over the entropy estimations of a specific area of memory into typical representations.
For on-chip measurements of bacterial growth, estimations for a given concentration were made using at least 10 randomly selected colonies.
To assess the estimation uncertainty of a given quantity, the root mean square error (RMSE) has been used.
Psychometric information can be thought of as a measure of discrimination (or precision of estimation) at a given point along the trait spectrum, and depends on both the slope and category parameters [ 32].
The simulation of the sampling was carried out using the Markov chain in Step (1), and produce the sequence x(1), …, x(n); (3) The estimation of expectation of a given function f(x) is (frac{1}{n - m}sumlimits_{t = m + 1}^{n} {f varvec{x}(t))}), from sequence points m to n. .
The simulation of the sampling was carried out using the Markov chain in Step (1), and produce the sequence x(1), …, x(n); The estimation of expectation of a given function f(x) is (frac{1}{n - m}sumlimits_{t = m + 1}^{n} {f varvec{x}(t))}), from sequence points m to n.
