Sentence examples for matrix decomposition is from inspiring English sources

Explicit expressions of desired non-fragile state feedback controllers are also given, and no matrix decomposition is required.

The DFT-based approach of polynomial matrix decomposition is capable of decomposing a matrix with either of these properties with small modification.

Matrix decomposition is used to show that the 2D 4×4 forward/inverse integer transform of two independent data blocks can be obtained from one 2D 8×8 forward/inverse integer transform circuit.

The primary reason of using the singular values in matrix decomposition is their robustness to defects in the matrix elements, which is not a case of own values in non-symmetric matrices [31].

The relation between polynomial matrix decomposition and DFT matrix decomposition is formulated in Section 2. In Section 3, two important spectral properties of decomposition, namely spectral majorization and smooth decomposition, are provided using appropriate arrangement of singular values (eigenvalues) and corresponding singular vectors (eigenvectors).

As the largest data set in our case is a 80×8080 matrix, using GPGPU to split the matrix decomposition is not suitable according to the results in Table 1 from [24].

The equality of polynomial matrix and dft matrix decomposed matrices decompositions are guaranteed via the finite duration constraint, which is investigated in Section 4. The finite duration constraint imposes the phase angles of singular vector (eigenvector) to minimize a nonlinear quadratic function.

For a given matrix, its spectral decomposition is (2.1).

(ii) NMF matrix decomposition method is applied to the TF matrix, and 10 base and coefficient components (i.e., W and H, and r=10) are computed for each signal.

Then, each of the matrix decomposition method is applied and the respective dictionaries learned.

The QR matrix decomposition of is used to achieve this goal [27].