Sentence examples for matrix and applying from inspiring English sources

Hence, the main purpose of this study was the development of a new affinity chromatographic strategy by using an O-phospho-l-tyrosine matrix and applying Box Behnken design (BBD) to obtain pre-miR-29 with high purity degree and yield, envisioning its application in gene therapy.

Subsequent PCs are fitted by subtracting the rank one approximation corresponding to the estimated sparse PC from the data matrix and applying the algorithm to the residual matrix.

Instead, a generalized information criterion (GIC) according to Kim et al. (2012) is applied: (10) GIC = ‖ X − d u v T ‖ F 2 n p σ ^ 2 + d ^ f log (log (n p ) ) log (p ) n p, Further PCs can be fitted by subtracting the rank one approximation, i.e. the estimated sparse PC, from the data matrix and applying the algorithm to the resulting residual matrix.

(v) IPS1: apply PCA to a each phoneme data matrix and apply PCA to the data matrix   (vi) IPS2: apply PCA to a each phoneme data matrix and apply ICA to the data matrix  .

Step 6 Convert the 1-D bit sequence to a matrix and apply the inverse Arnold transform to descramble the matrix using the correct key.  .

Now, taking the square root inverse of the constrained correlation matrix and apply normalisation, W kb = R ¯ kb − 1 2 (6) W kb = W kb W kb (7).

Step 2. Initial projection: for a chosen number of measurement, create a random projection matrix and apply it to the signals, obtaining, for all, Compute the equivalent dictionary.

Consequently, conservation measures for these species should simultaneously involve patch size, isolation and landscape matrix and apply to the entire metapopulation rather than to particular patches.

Our approach uses a ridge regularization to overcome the singularity of the sample covariance matrix and applies a soft-thresholding technique to reduce random noise and improve the testing power.

We describe an implicitly restarted block Lanczos method designed for the computation of a few extreme multiple or close eigenvalues and associated eigenvectors of a large sparse symmetric matrix and apply this method to determine the desired null space.

Without requiring of training data, we can efficiently design the robust projection matrix and apply it for most of CS systems, like a CS system for image processing with a conventional wavelet dictionary in which the SRE matrix is generally not available.