linear grow of square matrix in Vietnamese

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@Chuyên ngành kỹ thuật
@Lĩnh vực: toán & tin
-nhóm tuyến tính các ma trận vuông

Sentence patterns related to "linear grow of square matrix"

1. The cofactor matrix of a square matrix A is the matrix of Cofactors of A

2. Solving Linear Equations with Matrix Algebra

3. Use our online Adjoint matrix calculator to find the adjugate matrix of the square matrix.

4. Adjoint matrix Compute the classical Adjoint (also called adjugate) of a square matrix

5. Adjoint definition, a square matrix obtained from a given square matrix and having the property that its product with the given matrix is equal to the determinant of …

6. Adjoint of a Matrix Let A = [ a i j ] be a square matrix of order n

7. The adjugate, classical Adjoint, or adjunct of a square matrix is the transpose of its cofactor matrix

8. A matrix with elements that are the Cofactors, term-by-term, of a given square matrix

9. Any square matrix can uniquely be written as sum of a symmetric and a skew-symmetric matrix.

10. A matrix is a rectangular array of numbers written between square brackets.

Một ma trận là một hình chữ nhật mảng của các con số bằng văn bản giữa các dấu ngoặc vuông.

11. Distributed decoupling dynamic matrix control strategy is obtained for linear unconstrained systems.

12. Apply linear Algebra to solve systems of linear equations, find paths in graph theory, and map rotations of points in space using matrix operations

13. In linear algebra terms, the use of a block matrix corresponds to having a linear mapping thought of in terms of corresponding 'bunches' of basis vectors.

14. The Matrix Template Library (MTL) is a linear algebra library for C++ programs.

15. Let A be a square matrix of order n, if the rank of matrix A is less than or equal to n-2, then the Adjoint of matrix A results in 0.

16. An Antisymmetric matrix, also known as a skew-symmetric or antimetric matrix, is a square matrix that satisfies the identity A=-A^(T) (1) where A^(T) is the matrix transpose

17. 7.4 Matrix Norms and Condition Numbers This section considers the accuracy of computed solutions to linear systems

18. In linear algebra, the singular-value decomposition (SVD) is a factorization of a real or complex matrix.

19. GLBPM takes the approach of having a non-linear path through a matrix of alternatives directly from GSBPM.

20. In probability theory and statistics, a Covariance matrix (also known as auto-Covariance matrix, dispersion matrix, variance matrix, or variance–Covariance matrix) is a square matrix giving the Covariance between each pair of elements of a given random vector.Any Covariance matrix is symmetric and positive semi-definite and its main diagonal contains variances (i.e., the Covariance of each

21. For this to make sense, we need A to be a square matrix.

22. Stated in terms of numerical linear algebra, we convert M to an orthogonal matrix, Q, using QR decomposition.

23. In linear algebra and the theory of matrices, the Schur complement of a block matrix is defined as follows.

24. An orthogonalization type algorithm is presented for the triangularization of the coefficient matrix of a system of linear algebraic equations.

25. Enter a rotation angle for the Linear, Axial, Ellipsoid, Square and Rectangle gradient types