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SingularValueDecomposition Class

Computes the singular value decomposition (SVD) of a real M-by-N matrix A.
Inheritance Hierarchy
SystemObject
  DotNumerics.LinearAlgebraSingularValueDecomposition

Namespace: DotNumerics.LinearAlgebra
Assembly: DWSIM.MathOps.DotNumerics (in DWSIM.MathOps.DotNumerics.dll) Version: 1.0.0.0 (1.0.0.0)
Syntax
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public sealed class SingularValueDecomposition
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The SingularValueDecomposition type exposes the following members.

Constructors
 NameDescription
Public methodSingularValueDecomposition Initializes a new instance of the SingularValues class.
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Methods
 NameDescription
Public methodComputeSVD(Matrix, Matrix) Computes the singular value decomposition (SVD) of a real M-by-N matrix A. The SVD is written A = U * S * transpose(V)
Public methodComputeSVD(Matrix, Vector) Computes the singular value decomposition (SVD) of a real M-by-N matrix A. The SVD is written A = U * S * transpose(V)
Public methodComputeSVD(Matrix, Matrix, Matrix, Matrix) Computes the singular value decomposition (SVD) of a real M-by-N matrix A. The SVD is written A = U * S * transpose(V)
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Fields
 NameDescription
Private field_dgesvd 
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Extension Methods
 NameDescription
Public Extension MethodGetEnumNames
(Defined by General)
Public Extension MethodIsValidDouble
(Defined by General)
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Remarks
The SVD is written A = U * S * transpose(V) where S is an M-by-N matrix which is zero except for its min(m,n) diagonal elements, U is an M-by-M orthogonal matrix, and V is an N-by-N orthogonal matrix. The diagonal elements of S are the singular values of A; they are real and non-negative, and are returned in descending order. The first min(m,n) columns of U and V are the left and right singular vectors of A. Note that the routine returns V**T, not V.
See Also