Singular Value Decomposition.
Decompose a matrix A, whose dimension is m×n into components U, Σ and VT, such that A = U × Σ × VT, where
Decompose a matrix A, whose dimension is m×n into components U, Σ and VT, such that A = U × Σ × VT, where
- Matrix U is an orthonormal matrix (its row and column vectors are orthonormal), such that U × UT = I. Its dimension is m×m.
- Matrix Σ is a rectangular diagonal matrix such that all of the elements on the diagonal are non-negative. Its dimension is m×n.
- Matrix V is an orthonormal matrix (its row and column vectors are orthonormal), such that V × VT = I. Its dimension is n×n.
- At this time, matrices are restricted to only real numbers matrices. However, complex eigenvalues or eigenvectors are allowed.
- Values are calculated with the precision of 10-14 but are shown rounded to 9 decimal places.
Dimension m×n of the matrix : ×
A =
We are working hard to finish it, and you will be able to use it soon.
We are working hard to finish it, and you will be able to use it soon.