mikera.matrixx.decompose

Class SVD

java.lang.Object

mikera.matrixx.decompose.SVD

public class SVD
extends Object

Public API class for SVD decomposition

Author:

Mike

Constructor Summary

Constructors

Constructor and Description
SVD()

Method Summary

Modifier and Type	Method and Description
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.
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.
static ISVDResult	decomposeCompact(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.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

SVD

public SVD()

Method Detail

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 M^TM and MM^T, where M is the input matrix. U is m by m, S is m by n, V is n by n.

Parameters:

A -

Returns:

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 M^TM and MM^T, 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:

decomposeCompact

public static ISVDResult decomposeCompact(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 M^TM and MM^T, 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 -

compact -

Returns: