Package org.ejml.interfaces.decomposition

Interface Summary

Interface	Description
BidiagonalDecomposition<T extends Matrix>	Computes a matrix decomposition such that: A = U*B*VT where A is m by n, U is orthogonal and m by m, B is an m by n bidiagonal matrix, V is orthogonal and n by n.
CholeskyDecomposition<MatrixType extends Matrix>	Cholesky decomposition for DenseMatrix64F.
CholeskyLDLDecomposition<MatrixType extends Matrix>	Cholesky LDLT decomposition for DenseMatrix64F.
DecompositionInterface<T extends Matrix>	An interface for performing matrix decompositions on a DenseMatrix64F.
EigenDecomposition<MatrixType extends Matrix>	This is a generic interface for computing the eigenvalues and eigenvectors of a matrix.
LUDecomposition<T extends Matrix>	LU Decomposition refactors the original matrix such that: PT*L*U = A where P is a pivot matrix, L is a lower triangular matrix, U is an upper triangular matrix and A is the original matrix.
QRDecomposition<T extends Matrix>	QR decompositions decompose a rectangular matrix 'A' such that 'A=QR'.
QRPDecomposition<T extends Matrix>	Similar to QRDecomposition but it can handle the rank deficient case by performing column pivots during the decomposition.
SingularValueDecomposition<T extends Matrix>	This is an abstract class for computing the singular value decomposition (SVD) of a matrix, which is defined as: A = U * W * V T where A is m by n, and U and V are orthogonal matrices, and W is a diagonal matrix.
TridiagonalSimilarDecomposition<MatrixType extends Matrix>	Finds the decomposition of a matrix in the form of: A = O*T*OT where A is a symmetric m by m matrix, O is an orthogonal matrix, and T is a tridiagonal matrix.