Sentence examples for matrices we used from inspiring English sources

To compute the train-train and train-test kernel matrices, we used the parameter free Χ 2 kernel for all features.

To check the consistency of the fuzzy pairwise comparison matrices, we used the consistency test auxiliary linear programming mentioned in Eqs.

The D H (Denavit–Hartenberg) coordinate transformation method was used to perform the robot position analysis, according to the transformation matrices, we used Matlab to calculate the robot position analysis.

During these experiments, we focused on the performance of the reconstructed one- and two-dimensional signals, where the dimensions of the random measurement matrices we used were reduced by t 2 times (t ≥ 1).

To calculate the underlying sample sizes of the correlation matrices, we used the conservative harmonic mean of the sample sizes of the respective matrix (e.g. Stajkovic et al. 2009; Viswesvaran and Ones 1995), leading to N = 1159 in the external model and N = 3363 in the internal model.

Given two genes in one of our expression matrices we used different quantitative measures of coexpression to construct independent sets of RCGs.

In symmetric block matrices, we use an asterisk ∗ to represent a term induced by symmetry.

For the transpose, transpose conjugate, and conjugate matrices, we use T, H, and ∗, respectively.

In symmetric block matrices, we use an asterisk " " to represent a term that is induced by symmetry and diag stands for a block-diagonal matrix.

From this pool of new matrices we use the criteria of sensitivity and specificity to select the best.

To evaluate similarity between two H matrices we use the Munkres algorithm to establish the minimum cost assignment.