Sentence examples for minimization of error from inspiring English sources

Finally, since the desired outcome of the movement measurements is a reliable estimate of body segment kinematics, state-of-the-art techniques proposed for minimization of error propagation arising from a cluster of external markers are described.

Results are presented for measures of array performance such as input signal power, directivity of sound radiation and accuracy of sound reproduction resulting from the application of conventional control methods such as minimization of error in mean squared pressure, maximization of energy difference and minimization of weighted pressure error and energy.

Thus, the trade-off between minimization of error and increase in postprocessing time must be considered appropriately before choosing the NFOC value for future studies.

For each probeset a vector of its expression values E is represented in the form E = Dβ + ϵ, where D is a design matrix, β is a vector of coefficients indicating values of each factor's actual influence on the analyzed probeset, ϵ is a vector of error, and model fitting consists in the minimization of "error term" ϵ by finding optimal coefficients β.

In order to make those data accessible, the individual data sets need to be collected, reviewed and harmonized in a number of aspects, including the systematic performance of plausibility checks, the minimization of error, the adaptation of the sequencing ranges and the standardized presentation (alignment and annotation) of the mtDNA haplotypes.

We formalize the minimization of error e n as the maximization of the probability of a count vector x n (derived by discretization of t n ) under a multinomial distribution whose probability vector over transcripts is x ^ n = α n c n + ∑ r = 1 R θ n, r b r (that is, x ^ n is a normalized reconstruction of the tumor profile x n based on the model parameters).

Convergence of the solution, i.e., minimization of errors in variable equations, must be sufficiently deep.

The minimization of errors and predefined objective function was done by applying Particle Swarm Optimization technique.

This study concerns the training of a neural network in multiple stages considering minimization of errors from multiple data/pattern resources.

The resulting kinetics equations were solved using ode45 solver function in MATLAB, where the rate constants of the proposed kinetic model were determined by minimization of errors based on the optimum criteria of statistical analysis and by comparing the component concentrations at maximum and at equilibrium.

The choice of parameters was carried out using "smart" enumeration and minimization of errors on the known data.