| 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. |
| BidiagonalDecomposition_F32<T extends Matrix> |
Implementation of
BidiagonalDecomposition for 32-bit floats |
| BidiagonalDecomposition_F64<T extends Matrix> |
Implementation of
BidiagonalDecomposition for 64-bit floats |
| CholeskyDecomposition<MatrixType extends Matrix> |
Cholesky decomposition.
|
| CholeskyDecomposition_F32<MatrixType extends Matrix> |
Implementation of
CholeskyDecomposition for 32-bit floats. |
| CholeskyDecomposition_F64<MatrixType extends Matrix> |
Implementation of
CholeskyDecomposition for 64-bit floats. |
| CholeskyLDLDecomposition<MatrixType extends Matrix> |
Cholesky LDLT decomposition.
|
| CholeskyLDLDecomposition_F32<MatrixType extends Matrix> |
Implementation of
CholeskyDecomposition for 32-bit floats. |
| CholeskyLDLDecomposition_F64<MatrixType extends Matrix> |
Implementation of
CholeskyDecomposition for 64-bit floats. |
| CholeskySparseDecomposition<MatrixType extends Matrix> | |
| CholeskySparseDecomposition_F64<MatrixType extends Matrix> |
Implementation of
CholeskySparseDecomposition for 64-bit floats. |
| DecompositionInterface<T extends Matrix> |
An interface for performing matrix decompositions.
|
| DecompositionSparseInterface<T extends Matrix> |
Decomposition for sparse matrices.
|
| EigenDecomposition<T extends Matrix> |
This is a generic interface for computing the eigenvalues and eigenvectors of a matrix.
|
| EigenDecomposition_F32<MatrixType extends Matrix> |
Implementation of
EigenDecomposition for 64-bit floats |
| EigenDecomposition_F64<MatrixType extends Matrix> |
Implementation of
EigenDecomposition for 32-bit floats |
| 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. |
| LUDecomposition_F32<T extends Matrix> |
Implementation of
LUDecomposition for 64-bit numbers |
| LUDecomposition_F64<T extends Matrix> |
Implementation of
LUDecomposition for 64-bit numbers |
| LUSparseDecomposition<MatrixType extends Matrix> | |
| LUSparseDecomposition_F64<T extends Matrix> |
Implementation of
LUSparseDecomposition for 64-bit numbers |
| 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. |
| QRPDecomposition_F32<T extends Matrix> |
Implementation of
QRPDecomposition for 3-bit floats |
| QRPDecomposition_F64<T extends Matrix> |
Implementation of
QRPDecomposition for 64-bit floats |
| QRSparseDecomposition<T extends Matrix> |
Sparse
QRDecomposition |
| 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. |
| SingularValueDecomposition_F32<T extends Matrix> |
Implementation of
SingularValueDecomposition for 64-bit floats. |
| SingularValueDecomposition_F64<T extends Matrix> |
Implementation of
SingularValueDecomposition for 64-bit floats. |
| 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. |
| TridiagonalSimilarDecomposition_F32<MatrixType extends Matrix> |
Implementation of
TridiagonalSimilarDecomposition for 32-bit floats |
| TridiagonalSimilarDecomposition_F64<MatrixType extends Matrix> |
Implementation of
TridiagonalSimilarDecomposition for 64-bit floats |