Sentence examples for the subsequent iteration from inspiring English sources

Exact(9)

Next, we utilize this intermediate estimate to update the covariance matrix R(c), which in turn is used to produce the BLUE for the subsequent iteration and so on: F BLUE [ k + 1 ] = ( A H R - 1 ( c ^ [ k ] ) A ) - 1 A H R - 1 ( c ^ [ k ] ), c ^ [ k + 1 ] = F BLUE [ k + 1 ] y. (17).

The smaller piece of the development cycle of a Scrum project is called "sprint" and is defined by iterations that can last 2 to 4 weeks, allowing the project in question to be versioned at the end of each sprint or to continue being improved in the subsequent iteration [19].

After each refinement cycle the new reference volume was either theresholded or segmented using the "floodfill" function in the SITUS software package [37] to select the spike-ACE2 structure and minimize the influence of neighbouring spikes in the reference structure that was used in the subsequent iteration of the projection match alignment.

The subsequent iteration is denoted by i = 0, 1, …, Iterationmax⁡.

Each iteration performs 100 independent samplings, and uses the top-scoring samples to compute the distribution of the weights for the subsequent iteration.

In the subsequent iteration, the algorithm continues with the creation of a new group with the first reaction in the updated reaction list.

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Similar(51)

As we noted in free expansion case, FM tended to distort the struts length at the beginning of the iterative process, correcting it in the course of the subsequent iterations (see Fig. 6(b), bottom left graph).

When there are more than one files input, the subsequent iterations are done only on the output data as opposed to adding the output data into the stack.

An optimal experiment design using the D-optimality criterion is formulated to provide "rich" experimental data tor improving parameter estimates in the subsequent iterations.

The subsequent iterations (2 4) themes were identified, sorted and further refined with questionnaires.

The file presents the set of parameters tested in the subsequent iterations of the optimization procedure with the analysis of classification accuracy values that they were providing.

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