definite matrix वाक्य
उदाहरण वाक्य
मोबाइल
- Let be a ( fixed ) positive definite matrix of size.
- Conversely, every positive semi-definite matrix is the covariance matrix of some multivariate distribution.
- If " M " is a positive definite matrix, this yields an inner product.
- With smooth and bounded coefficients and a positive definite matrix ( a _ { ij } ).
- Interval Finite Element Method require the solution of parameter dependent system of equations ( usually with symmetric positive definite matrix ).
- And the log-concavity of the determinant of a positive definite matrix implies that " D " = 1.
- We need to make " P " a positive semi-definite matrix in order to reformulate a convex function.
- A symmetric matrix and another symmetric and positive-definite matrix can be simultaneously diagonalized, although not necessarily via a similarity transformation.
- *For any real invertible matrix A, the product A ^ { \ mathrm { T } } A is a positive definite matrix.
- Every Hermitian positive-definite matrix ( and thus also every real-valued symmetric positive-definite matrix ) has a unique Cholesky decomposition.
- Every Hermitian positive-definite matrix ( and thus also every real-valued symmetric positive-definite matrix ) has a unique Cholesky decomposition.
- For every pixel ( i, j ) in the image, the structure tensor J is a symmetric and positive semi-definite matrix.
- The diffusion tensor, a 3 & times; 3 symmetric positive-definite matrix, offers a straightforward solution to both of these goals.
- *PM : square root of positive definite matrix, id = 7067-- WP guess : square root of positive definite matrix-- Status:
- *PM : square root of positive definite matrix, id = 7067-- WP guess : square root of positive definite matrix-- Status:
- Every real non-singular matrix can be uniquely factored as the product of an orthogonal matrix and a symmetric positive definite matrix, which is called a polar decomposition.
- Many of these methods are only applicable to certain types of equations, for example the Cholesky factorization and conjugate gradient will only work if is a positive definite matrix.
- Is negative definite for some positive definite matrix M = M ^ { T } . ( The relevant Lyapunov function is V ( x ) = x ^ TMx .)
- Mathematically this means that the result of subtracting the expected squared error ( which is not usually known ) from M is a semi-definite or positive-definite matrix.
- More generally, when " D " is a symmetric positive definite matrix, the equation describes anisotropic diffusion, which is written ( for three dimensional diffusion ) as:
- अधिक वाक्य: 1 2
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