For the determined A matrix is given below by Table 3.
For an image I(n1, n2) of size M × N, we can determine a matrix F I (k1, k2) also of size M × N that contains all the spatial frequency components of the image, for k1 ∈ {0,…, M - 1} and k2 ∈ {0,…, N - 1}.
The number of extracted features is reduced by linear discriminant analysis (LDA) that always determines a one-dimensional matrix containing distributions of spike and non-spike samples.
The techniques of determining a perturbation matrix from a knowledge of the original rate constant matrix and the experimental reaction paths are discussed.
The main idea is to determine a correction matrix, which once applied to the originally estimated (incorrect) dose distribution map, generates a corrected one, which better fits to the field measurements.
The SMM-BP algorithm was used to determine a scoring matrix of murine TAP specificity.
The shortest positive or negative paths among pairs of nodes can be used to determine a dependency matrix [ 10, 11, 32, 35] which reflects the long-range regulatory relationships among signaling components.
Dynamic programming applied to each resulting matrix determines a series of optimal local alignments which are then summed into a "summary" matrix to which dynamic programming is applied again to determine the overall structural alignment.
The information contained in this matrix determines a network's capacity of finely controlling the spatio-temporal organization of expression domains along the strip of nuclei modeled (patterning capabilities).
The principal minor determinants are used to determine if a matrix is positive or negative definite or semidefinite.
