IGLib
1.7.2
The IGLib base library EXTENDED - with other lilbraries and applications.
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Singular Value Decomposition. More...
Public Member Functions | |
SingularValueDecomposition (GeneralMatrix Arg) | |
Construct the singular value decomposition More... | |
virtual GeneralMatrix | GetU () |
Return the left singular vectors More... | |
virtual GeneralMatrix | GetV () |
Return the right singular vectors More... | |
virtual double | Norm2 () |
Two norm More... | |
virtual double | Condition () |
Two norm condition number More... | |
virtual int | Rank () |
Effective numerical matrix rank More... | |
SingularValueDecomposition (GeneralMatrix Arg) | |
Construct the singular value decomposition More... | |
virtual GeneralMatrix | GetU () |
Return the left singular vectors More... | |
virtual GeneralMatrix | GetV () |
Return the right singular vectors More... | |
virtual double | Norm2 () |
Two norm More... | |
virtual double | Condition () |
Two norm condition number More... | |
virtual int | Rank () |
Effective numerical matrix rank More... | |
Properties | |
virtual double[] | SingularValues [get] |
Return the one-dimensional array of singular values More... | |
virtual GeneralMatrix | S [get] |
Return the diagonal matrix of singular values More... | |
Private Member Functions | |
void ISerializable. | GetObjectData (SerializationInfo info, StreamingContext context) |
void ISerializable. | GetObjectData (SerializationInfo info, StreamingContext context) |
Private Attributes | |
double[][] | U |
Arrays for internal storage of U and V. internal storage of U. internal storage of V. More... | |
double[][] | V |
double[] | s |
Array for internal storage of singular values. internal storage of singular values. More... | |
int | m |
Row and column dimensions. row dimension. column dimension. More... | |
int | n |
Singular Value Decomposition.
For an m-by-n matrix A with m >= n, the singular value decomposition is an m-by-n orthogonal matrix U, an n-by-n diagonal matrix S, and an n-by-n orthogonal matrix V so that A = U*S*V'.
The singular values, sigma[k] = S[k][k], are ordered so that sigma[0] >= sigma[1] >= ... >= sigma[n-1].
The singular value decompostion always exists, so the constructor will never fail. The matrix condition number and the effective numerical rank can be computed from this decomposition.
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inline |
Construct the singular value decomposition
Arg | Rectangular matrix |
References DotNetMatrix.GeneralMatrix.ArrayCopy, DotNetMatrix.GeneralMatrix.ColumnDimension, DotNetMatrix.SingularValueDecomposition.m, DotNetMatrix.SingularValueDecomposition.n, and DotNetMatrix.GeneralMatrix.RowDimension.
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inline |
Construct the singular value decomposition
Arg | Rectangular matrix |
References DotNetMatrix.GeneralMatrix.ArrayCopy, DotNetMatrix.GeneralMatrix.ColumnDimension, DotNetMatrix.SingularValueDecomposition.m, DotNetMatrix.SingularValueDecomposition.n, and DotNetMatrix.GeneralMatrix.RowDimension.
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inlinevirtual |
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inlinevirtual |
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inlinevirtual |
Two norm
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inlinevirtual |
Two norm condition number
Referenced by DotNetMatrix.GeneralMatrix.Condition().
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inlinevirtual |
Effective numerical matrix rank
Referenced by DotNetMatrix.GeneralMatrix.Rank().
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inlineprivate |
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inlinevirtual |
Return the left singular vectors
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inlinevirtual |
Return the right singular vectors
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inlinevirtual |
Two norm
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inlinevirtual |
Two norm condition number
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inlinevirtual |
Effective numerical matrix rank
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inlineprivate |
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private |
Arrays for internal storage of U and V. internal storage of U. internal storage of V.
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private |
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private |
Array for internal storage of singular values. internal storage of singular values.
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private |
Row and column dimensions. row dimension. column dimension.
Referenced by DotNetMatrix.SingularValueDecomposition.SingularValueDecomposition().
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private |
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get |
Return the one-dimensional array of singular values
Referenced by DotNetMatrix.test.TestMatrix.Main().
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get |
Return the diagonal matrix of singular values
Referenced by DotNetMatrix.test.TestMatrix.Main().