Uses of Package
org.ejml.alg.dense.decomposition

Packages that use org.ejml.alg.dense.decomposition
org.ejml.alg.block.decomposition.chol   
org.ejml.alg.block.decomposition.hessenberg   
org.ejml.alg.block.decomposition.qr   
org.ejml.alg.dense.decomposition   
org.ejml.alg.dense.decomposition.bidiagonal   
org.ejml.alg.dense.decomposition.chol   
org.ejml.alg.dense.decomposition.eig   
org.ejml.alg.dense.decomposition.hessenberg   
org.ejml.alg.dense.decomposition.lu   
org.ejml.alg.dense.decomposition.qr   
org.ejml.alg.dense.decomposition.svd   
org.ejml.alg.dense.linsol.qr   
org.ejml.ops   
org.ejml.simple   
 

Classes in org.ejml.alg.dense.decomposition used by org.ejml.alg.block.decomposition.chol
CholeskyDecomposition
           Cholesky decomposition for DenseMatrix64F.
DecompositionInterface
           An interface for performing matrix decompositions on a DenseMatrix64F.
 

Classes in org.ejml.alg.dense.decomposition used by org.ejml.alg.block.decomposition.hessenberg
DecompositionInterface
           An interface for performing matrix decompositions on a DenseMatrix64F.
 

Classes in org.ejml.alg.dense.decomposition used by org.ejml.alg.block.decomposition.qr
DecompositionInterface
           An interface for performing matrix decompositions on a DenseMatrix64F.
QRDecomposition
           QR decompositions decompose a rectangular matrix 'A' such that 'A=QR'.
 

Classes in org.ejml.alg.dense.decomposition used by org.ejml.alg.dense.decomposition
CholeskyDecomposition
           Cholesky decomposition for DenseMatrix64F.
DecompositionInterface
           An interface for performing matrix decompositions on a DenseMatrix64F.
EigenDecomposition
           This is a generic interface for computing the eigenvalues and eigenvectors of a matrix.
LUDecomposition
           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
           QR decompositions decompose a rectangular matrix 'A' such that 'A=QR'.
QRPDecomposition
           Similar to QRDecomposition but it can handle the rank deficient case by performing column pivots during the decomposition.
SingularValueDecomposition
           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.
 

Classes in org.ejml.alg.dense.decomposition used by org.ejml.alg.dense.decomposition.bidiagonal
DecompositionInterface
           An interface for performing matrix decompositions on a DenseMatrix64F.
 

Classes in org.ejml.alg.dense.decomposition used by org.ejml.alg.dense.decomposition.chol
BaseDecompositionBlock64
          Generic interface for wrapping a BlockMatrix64F decomposition for processing of DenseMatrix64F.
CholeskyDecomposition
           Cholesky decomposition for DenseMatrix64F.
DecompositionInterface
           An interface for performing matrix decompositions on a DenseMatrix64F.
 

Classes in org.ejml.alg.dense.decomposition used by org.ejml.alg.dense.decomposition.eig
DecompositionInterface
           An interface for performing matrix decompositions on a DenseMatrix64F.
EigenDecomposition
           This is a generic interface for computing the eigenvalues and eigenvectors of a matrix.
 

Classes in org.ejml.alg.dense.decomposition used by org.ejml.alg.dense.decomposition.hessenberg
BaseDecompositionBlock64
          Generic interface for wrapping a BlockMatrix64F decomposition for processing of DenseMatrix64F.
DecompositionInterface
           An interface for performing matrix decompositions on a DenseMatrix64F.
 

Classes in org.ejml.alg.dense.decomposition used by org.ejml.alg.dense.decomposition.lu
DecompositionInterface
           An interface for performing matrix decompositions on a DenseMatrix64F.
LUDecomposition
           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.
 

Classes in org.ejml.alg.dense.decomposition used by org.ejml.alg.dense.decomposition.qr
BaseDecompositionBlock64
          Generic interface for wrapping a BlockMatrix64F decomposition for processing of DenseMatrix64F.
DecompositionInterface
           An interface for performing matrix decompositions on a DenseMatrix64F.
QRDecomposition
           QR decompositions decompose a rectangular matrix 'A' such that 'A=QR'.
QRPDecomposition
           Similar to QRDecomposition but it can handle the rank deficient case by performing column pivots during the decomposition.
 

Classes in org.ejml.alg.dense.decomposition used by org.ejml.alg.dense.decomposition.svd
DecompositionInterface
           An interface for performing matrix decompositions on a DenseMatrix64F.
SingularValueDecomposition
           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.
 

Classes in org.ejml.alg.dense.decomposition used by org.ejml.alg.dense.linsol.qr
QRDecomposition
           QR decompositions decompose a rectangular matrix 'A' such that 'A=QR'.
QRPDecomposition
           Similar to QRDecomposition but it can handle the rank deficient case by performing column pivots during the decomposition.
 

Classes in org.ejml.alg.dense.decomposition used by org.ejml.ops
EigenDecomposition
           This is a generic interface for computing the eigenvalues and eigenvectors of a matrix.
SingularValueDecomposition
           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.
 

Classes in org.ejml.alg.dense.decomposition used by org.ejml.simple
EigenDecomposition
           This is a generic interface for computing the eigenvalues and eigenvectors of a matrix.
SingularValueDecomposition
           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.
 



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