Interface SVD<T>

  • All Known Implementing Classes:
    SVD

    public interface SVD<T>
    Singular Value Decomposition.

    For an m-by-n matrix A, the singular value decomposition is an m-by-(m or n) orthogonal matrix U, a (m or 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.

    • Field Detail

      • INSTANCE

        static final SVD<Matrix> INSTANCE
      • MATRIXSMALLSINGLETHREADED

        static final SVD<Matrix> MATRIXSMALLSINGLETHREADED
      • MATRIXLARGESINGLETHREADED

        static final SVD<Matrix> MATRIXLARGESINGLETHREADED
      • MATRIXSMALLMULTITHREADED

        static final SVD<Matrix> MATRIXSMALLMULTITHREADED
      • MATRIXLARGEMULTITHREADED

        static final SVD<Matrix> MATRIXLARGEMULTITHREADED
    • Method Detail

      • calc

        T[] calc​(T source)