Click or drag to resize

FloatComplexSVDecomp Class

Class FloatComplexSVDecomp represents the singular value decomposition (SVD) of a matrix.
Inheritance Hierarchy
SystemObject
  CenterSpace.NMath.CoreFloatComplexSVDecomp

Namespace:  CenterSpace.NMath.Core
Assembly:  NMath (in NMath.dll) Version: 7.4
Syntax
[SerializableAttribute]
public class FloatComplexSVDecomp : ICloneable

The FloatComplexSVDecomp type exposes the following members.

Constructors
  NameDescription
Public methodFloatComplexSVDecomp
Constructs an empty singular value decomposition instance.
Public methodFloatComplexSVDecomp(FloatComplexMatrix)
Constructs a singular value decomposition of a given matrix.
Top
Properties
  NameDescription
Public propertyCols
Gets the number of columns in the matrix that the decomposition represents.
Public propertyFail
Gets the status of the decomposition.
Public propertyLeftVectors
Gets the matrix whose columns are the left singular vectors of this decomposition.
Public propertyNumberLeftVectors
Gets the number of left singular vectors in the decomposition.
Public propertyNumberRightVectors
Gets the number of right singular vectors in the decomposition.
Public propertyRank
Gets the rank of the matrix which this decomposition represents.
Public propertyRightVectors
Gets the matrix whose columns are the right singular vectors of this decomposition.
Public propertyRows
Gets the number of rows in the matrix that this decomposition represents.
Public propertySingularValues
Gets the singular values of this decomposition. The values are non-negative and arranged in decreasing order.
Top
Methods
  NameDescription
Public methodClone
Creates a deep copy of this decomposition.
Public methodFactor
Builds a decomposition for the matrix A.
Public methodLeftVector
Returns the specified left singular vector.
Public methodRightVector
Returns the specified right singular vector.
Public methodSingularValue
Returns the specified singular value.
Public methodTruncate
Truncates all singular values that are less than a given tolerance by setting them to zero.
Top
Remarks
The singular value decomposition is a representation of a matrix A of the form:
A = USV'
where U and V are orthogonal, S is diagonal, and V' denotes the transpose of the matrix V. The entries along the diagonal of S are the singular values. The columns of U are the left singular vectors, and the columns of V are the right singular vectors. By default, the reduced singular value decomposition and all singular vectors are computed. If you want the full singular value decomposition, or just the singular values computed, use class DoubleSVDecompServer.
See Also