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Perform Singular Value Decomposition. More...
| Functions | |
| AFAPI void | svd (array &u, array &s, array &vt, const array &in) | 
| C++ Interface for SVD decomposition.  More... | |
| AFAPI void | svdInPlace (array &u, array &s, array &vt, array &in) | 
| C++ Interface for SVD decomposition.  More... | |
| AFAPI af_err | af_svd (af_array *u, af_array *s, af_array *vt, const af_array in) | 
| C Interface for SVD decomposition.  More... | |
| AFAPI af_err | af_svd_inplace (af_array *u, af_array *s, af_array *vt, af_array in) | 
| C Interface for SVD decomposition.  More... | |
Perform Singular Value Decomposition.
This function factorizes a matrix A into two unitary matrices U and Vt, and a diagonal matrix S such that
\(A = U * S * Vt\)
If A has M rows and N columns, U is of the size M x M , V is of size N x N, and S is of size M x N
The arrayfire function only returns the non zero diagonal elements of S. To reconstruct the original matrix A from the individual factors, the following code snuppet can be used:
When memory is a concern, and A is dispensible, svdInPlace() can be used
C Interface for SVD decomposition.
| [out] | u | is the output array containing U | 
| [out] | s | is the output array containing the diagonal values of sigma, (singular values of the input matrix)) | 
| [out] | vt | is the output array containing V^H | 
| [in] | in | is the input matrix | 
C Interface for SVD decomposition.
| [out] | u | is the output array containing U | 
| [out] | s | is the output array containing the diagonal values of sigma, (singular values of the input matrix)) | 
| [out] | vt | is the output array containing V^H | 
| [in,out] | in | is the input matrix that will contain random data after this operation | 
C++ Interface for SVD decomposition.
| [out] | u | is the output array containing U | 
| [out] | s | is the output array containing the diagonal values of sigma, (singular values of the input matrix)) | 
| [out] | vt | is the output array containing V^H | 
| [in] | in | is the input matrix | 
C++ Interface for SVD decomposition.
| [out] | u | is the output array containing U | 
| [out] | s | is the output array containing the diagonal values of sigma, (singular values of the input matrix)) | 
| [out] | vt | is the output array containing V^H | 
| [in,out] | in | is the input matrix and will contain random data after this operation |