mikera.matrixx.decompose
Class SVD
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- mikera.matrixx.decompose.SVD
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public class SVD extends java.lang.ObjectPublic API class for SVD decomposition
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Method Summary
All Methods Static Methods Concrete Methods Modifier and Type Method and Description static ISVDResultdecompose(AMatrix A)Computes the Singular Value Decomposition of a matrix, which is the decomposition of the given matrix A as: A = U*S*V, where U and V are orthogonal and S is a diagonal matrix containing singular values along its diagonal.static ISVDResultdecompose(AMatrix A, boolean compact)Computes the Singular Value Decomposition of a matrix, which is the decomposition of the given matrix A as: A = U*S*V, where U and V are orthogonal and S is a diagonal matrix containing singular values along its diagonal.static ISVDResultdecomposeCompact(AMatrix A)Computes the compact Singular Value Decomposition of a matrix, which is the decomposition of the given matrix A as: A = U*S*V, where U and V are orthogonal and S is a diagonal matrix containing singular values along its diagonal.static ISVDResultdecomposeNonZero(AMatrix A)Computes the singular value decomposition, keeping only non-zero singular values
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Method Detail
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decompose
public static ISVDResult decompose(AMatrix A)
Computes the Singular Value Decomposition of a matrix, which is the decomposition of the given matrix A as: A = U*S*V, where U and V are orthogonal and S is a diagonal matrix containing singular values along its diagonal. The non zero singular values are the square roots of the non-zero eigenvalues of MTM and MMT, where M is the input matrix. U is m by m, S is m by n, V is n by n.- Parameters:
A-- Returns:
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decompose
public static ISVDResult decompose(AMatrix A, boolean compact)
Computes the Singular Value Decomposition of a matrix, which is the decomposition of the given matrix A as: A = U*S*V, where U and V are orthogonal and S is a diagonal matrix containing singular values along its diagonal. The non zero singular values are the square roots of the non-zero eigenvalues of MTM and MMT, where M is the input matrix. If compact is false, U is m by m, W is m by n, V is n by n, if compact is true, U is m by s, S is s by s, and V is n by s, where s is the number of Singular Values- Parameters:
A-compact-- Returns:
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decomposeCompact
public static ISVDResult decomposeCompact(AMatrix A)
Computes the compact Singular Value Decomposition of a matrix, which is the decomposition of the given matrix A as: A = U*S*V, where U and V are orthogonal and S is a diagonal matrix containing singular values along its diagonal. The non zero singular values are the square roots of the non-zero eigenvalues of MTM and MMT, where M is the input matrix. U is m by s, S is s by s, and V is n by s, where s is the number of Singular Values- Parameters:
A-- Returns:
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decomposeNonZero
public static ISVDResult decomposeNonZero(AMatrix A)
Computes the singular value decomposition, keeping only non-zero singular values- Parameters:
A-- Returns:
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