Package org.jblas
Class Singular
- java.lang.Object
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- org.jblas.Singular
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public class Singular extends java.lang.Object
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Constructor Summary
Constructors Constructor Description Singular()
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Method Summary
All Methods Static Methods Concrete Methods Modifier and Type Method Description static ComplexDoubleMatrix[]
fullSVD(ComplexDoubleMatrix A)
Compute a singular-value decomposition of A.static ComplexFloatMatrix[]
fullSVD(ComplexFloatMatrix A)
Compute a singular-value decomposition of A.static DoubleMatrix[]
fullSVD(DoubleMatrix A)
Compute a singular-value decomposition of A.static FloatMatrix[]
fullSVD(FloatMatrix A)
Compute a singular-value decomposition of A.static ComplexDoubleMatrix[]
sparseSVD(ComplexDoubleMatrix A)
Compute a singular-value decomposition of A (sparse variant).static ComplexFloatMatrix[]
sparseSVD(ComplexFloatMatrix A)
Compute a singular-value decomposition of A (sparse variant).static DoubleMatrix[]
sparseSVD(DoubleMatrix A)
Compute a singular-value decomposition of A (sparse variant).static FloatMatrix[]
sparseSVD(FloatMatrix A)
Compute a singular-value decomposition of A (sparse variant).static DoubleMatrix
SVDValues(ComplexDoubleMatrix A)
Compute the singular values of a complex matrix.static FloatMatrix
SVDValues(ComplexFloatMatrix A)
Compute the singular values of a complex matrix.static DoubleMatrix
SVDValues(DoubleMatrix A)
Compute the singular values of a matrix.static FloatMatrix
SVDValues(FloatMatrix A)
Compute the singular values of a matrix.
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Constructor Detail
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Singular
public Singular()
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Method Detail
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fullSVD
public static DoubleMatrix[] fullSVD(DoubleMatrix A)
Compute a singular-value decomposition of A.- Returns:
- A DoubleMatrix[3] array of U, S, V such that A = U * diag(S) * V'
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sparseSVD
public static DoubleMatrix[] sparseSVD(DoubleMatrix A)
Compute a singular-value decomposition of A (sparse variant). Sparse means that the matrices U and V are not square but only have as many columns (or rows) as necessary.- Parameters:
A
-- Returns:
- A DoubleMatrix[3] array of U, S, V such that A = U * diag(S) * V'
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sparseSVD
public static ComplexDoubleMatrix[] sparseSVD(ComplexDoubleMatrix A)
Compute a singular-value decomposition of A (sparse variant). Sparse means that the matrices U and V are not square but only have as many columns (or rows) as necessary.- Parameters:
A
-- Returns:
- A ComplexDoubleMatrix[3] array of U, S, V such that A = U * diag(S) * V*
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fullSVD
public static ComplexDoubleMatrix[] fullSVD(ComplexDoubleMatrix A)
Compute a singular-value decomposition of A.- Returns:
- A ComplexDoubleMatrix[3] array of U, S, V such that A = U * diag(S) * V'
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SVDValues
public static DoubleMatrix SVDValues(DoubleMatrix A)
Compute the singular values of a matrix.- Parameters:
A
- DoubleMatrix of dimension m * n- Returns:
- A min(m, n) vector of singular values.
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SVDValues
public static DoubleMatrix SVDValues(ComplexDoubleMatrix A)
Compute the singular values of a complex matrix.- Parameters:
A
- ComplexDoubleMatrix of dimension m * n- Returns:
- A real-valued (!) min(m, n) vector of singular values.
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fullSVD
public static FloatMatrix[] fullSVD(FloatMatrix A)
Compute a singular-value decomposition of A.- Returns:
- A FloatMatrix[3] array of U, S, V such that A = U * diag(S) * V'
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sparseSVD
public static FloatMatrix[] sparseSVD(FloatMatrix A)
Compute a singular-value decomposition of A (sparse variant). Sparse means that the matrices U and V are not square but only have as many columns (or rows) as necessary.- Parameters:
A
-- Returns:
- A FloatMatrix[3] array of U, S, V such that A = U * diag(S) * V'
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sparseSVD
public static ComplexFloatMatrix[] sparseSVD(ComplexFloatMatrix A)
Compute a singular-value decomposition of A (sparse variant). Sparse means that the matrices U and V are not square but only have as many columns (or rows) as necessary.- Parameters:
A
-- Returns:
- A ComplexFloatMatrix[3] array of U, S, V such that A = U * diag(S) * V*
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fullSVD
public static ComplexFloatMatrix[] fullSVD(ComplexFloatMatrix A)
Compute a singular-value decomposition of A.- Returns:
- A ComplexFloatMatrix[3] array of U, S, V such that A = U * diag(S) * V'
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SVDValues
public static FloatMatrix SVDValues(FloatMatrix A)
Compute the singular values of a matrix.- Parameters:
A
- FloatMatrix of dimension m * n- Returns:
- A min(m, n) vector of singular values.
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SVDValues
public static FloatMatrix SVDValues(ComplexFloatMatrix A)
Compute the singular values of a complex matrix.- Parameters:
A
- ComplexFloatMatrix of dimension m * n- Returns:
- A real-valued (!) min(m, n) vector of singular values.
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