Documentation of 'mikera.matrixx.decompose.SVD' Java class
SVD
mikera.matrixx.decompose

Class SVD



  • public class SVD
    extends java.lang.Object
    Public API class for SVD decomposition
    • Method Summary

      All Methods Static Methods Concrete Methods 
      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 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 ISVDResult decomposeNonZero(AMatrix A)
      Computes the singular value decomposition, keeping only non-zero singular values
      • Methods inherited from class java.lang.Object

        equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
    • 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 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:
      • 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:
      • 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:
      • 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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