| 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.
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| BidiagonalDecomposition_F32<T extends Matrix> |
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| BidiagonalDecomposition_F64<T extends Matrix> |
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| CholeskyDecomposition<MatrixType extends Matrix> |
Cholesky decomposition.
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| CholeskyDecomposition_F32<MatrixType extends Matrix> |
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| CholeskyDecomposition_F64<MatrixType extends Matrix> |
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| CholeskyLDLDecomposition<MatrixType extends Matrix> |
Cholesky LDLT decomposition.
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| CholeskyLDLDecomposition_F32<MatrixType extends Matrix> |
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| CholeskyLDLDecomposition_F64<MatrixType extends Matrix> |
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| CholeskySparseDecomposition<MatrixType extends Matrix> |
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| CholeskySparseDecomposition_F32<MatrixType extends Matrix> |
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| CholeskySparseDecomposition_F64<MatrixType extends Matrix> |
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| DecompositionInterface<T extends Matrix> |
An interface for performing matrix decompositions.
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| DecompositionSparseInterface<T extends Matrix> |
Decomposition for sparse matrices.
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| EigenDecomposition<T extends Matrix> |
This is a generic interface for computing the eigenvalues and eigenvectors of a matrix.
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| EigenDecomposition_F32<MatrixType extends Matrix> |
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| EigenDecomposition_F64<MatrixType extends Matrix> |
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| 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.
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| LUDecomposition_F32<T extends Matrix> |
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| LUDecomposition_F64<T extends Matrix> |
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| LUSparseDecomposition<MatrixType extends Matrix> |
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| LUSparseDecomposition_F32<T extends Matrix> |
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| LUSparseDecomposition_F64<T extends Matrix> |
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| QRDecomposition<T extends Matrix> |
QR decompositions decompose a rectangular matrix 'A' such that 'A=QR'.
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| 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> |
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| QRPDecomposition_F64<T extends Matrix> |
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| QRSparseDecomposition<T extends Matrix> |
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| 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.
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| SingularValueDecomposition_F32<T extends Matrix> |
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| SingularValueDecomposition_F64<T extends Matrix> |
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| 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.
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| TridiagonalSimilarDecomposition_F32<MatrixType extends Matrix> |
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| TridiagonalSimilarDecomposition_F64<MatrixType extends Matrix> |
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