Sentence examples for minimizing the approximate from inspiring English sources

Finally, the defect structure at a finite temperature is obtained by minimizing the approximate Helmholtz free energy.

Assuming the use of full-diversity space-time codes, we derive two power allocation strategies minimizing the approximate SER expressions, for constrained transmit power.

For minimizing the approximate error, uniform design sampling, online incremental learning and cross-validation are used in the learning process of RVMs.

To this end, we calculate the optimally stable hydrophobicity profile, that minimizes the approximate effective free energy Eq. (16), for a given contact matrix, with a large normalized energy gap.

The approximate line of the periodicity was calculated using the highest peak (statistic significance) of the periodogram and was fitted by minimizing the square error between the approximate line and the series of expression values.

Following the work of Natoli and Ceperley, the division between the direct- and reciprocal-space terms is optimized by minimizing the squared deviation of the approximate representation from the exact form.

Different from the trivial resampling scheme for SSML channel models, an optimum resampling method is proposed in[14] for MSML channels, which aims at minimizing the average error of approximating the MSML channel by an SSML model.

(14) The pmf on c is given by the recursion (15) with P c(1 | g,1) = 1 and P c(c | g,1) = 0 for c ≠ 1. P S(S | c) is approximated by minimizing the number, m, of mutations over the assignments of observed sequences to c groups.

The approximate polynomials are obtained by minimizing the error in the propagation.

A traditional BPN is normally trained by minimizing the absolute difference between target outputs and approximate outputs.

This method takes a series of data points (u i,v i ) with i = 1,…, N and attempts to find a function G u i ) whose output ṽ i closely approximates v i by minimizing the sum of the squares error between the points (u i, ṽ i ) and their corresponding points (u i,v i ) in the data.