Sentence examples for matrix reduction technique from inspiring English sources

A powerful matrix reduction technique is developed to analyze rotor-bearing systems, by using the modal data of the isotropic undamped stationary parts.

Monga introduced another dimension reduction technique, called nonnegative matrix factorization (NMF) [15], into their new hashing algorithm [16].

Matrix factorization is also a dimensionality reduction technique as it reduces the sample dimension from m to k in the space of U.

To solve this problem, we adapted the non-negative matrix factorization (NMF) algorithm, a dimension reduction technique first developed for image processing (Lee and Seung, 1999) that has subsequently gained popularity in processing high-dimensional biological data, such as microarrays (Carmona-Saez et al., 2006; Kim and Tidor, 2003; Pascual-Montano et al., 2006b).

The method is based on the Arnoldi modal reduction technique that uses orthogonal matrix transformations to reduce the discretized transport equations.

In NMF hashing, the dimension reduction technique is based on the approximative nonnegative matrix factorization, which factorizes the image matrix into two lower rank matrices.

Optionally, the distance matrix may be obtained from the leading dimensions of a data reduction technique, performed to keep the most informative parts of the data while excluding noise.

The other two models applied principal component analysis as the dimension reduction technique: one based on eigenvalues of a genetic correlation matrix and the other on eigenvalues of a combined lactation matrix.

The reduction technique assumes a separable parameter dependence of the full system matrices and the initial condition.

Due to the fact that the number of genes was larger than the number of samples, a dimension reduction technique called singular value decomposition (SVD) was performed on the gene expression matrix X [ 6].

Iterated IIRS method is an efficient reduction technique because the highly accurate eigenproperties from the repeatedly updated condensed matrices can be obtained without consuming expensive computational cost.