Name | Description | Type | Package | Framework |
BidiagonalDecompositionTall_D64 | BidiagonalDecomposition specifically designed for tall matrices. | Class | org.ejml.alg.dense.decomposition.bidiagonal | Ejml ( Efficient Java Matrix Library ) |
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BidiagonalDecompositionRow_D64 | Performs a BidiagonalDecomposition using householder reflectors. | Class | org.ejml.alg.dense.decomposition.bidiagonal | Ejml ( Efficient Java Matrix Library ) |
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BaseDecomposition_B64_to_D64 | Generic interface for wrapping a BlockMatrix64F decomposition for processing of DenseMatrix64F. | Class | org.ejml.alg.dense.decomposition | Ejml ( Efficient Java Matrix Library ) |
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CholeskyDecomposition_B64_to_D64 | Wrapper around CholeskyOuterForm_B64 that allows it to process DenseMatrix64F. | Class | org.ejml.alg.dense.decomposition.chol | Ejml ( Efficient Java Matrix Library ) |
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CholeskyDecompositionBlock_D64 | This is an implementation of Cholesky that processes internal submatrices as blocks. | Class | org.ejml.alg.dense.decomposition.chol | Ejml ( Efficient Java Matrix Library ) |
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CholeskyDecompositionCommon_D64 | This is an abstract class for a Cholesky decomposition. | Class | org.ejml.alg.dense.decomposition.chol | Ejml ( Efficient Java Matrix Library ) |
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CholeskyDecompositionInner_D64 | This implementation of a Cholesky decomposition using the inner-product form. | Class | org.ejml.alg.dense.decomposition.chol | Ejml ( Efficient Java Matrix Library ) |
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CholeskyDecompositionLDL_D64 | This variant on the Cholesky decomposition avoid the need to take the square root by performing the following decomposition: | Class | org.ejml.alg.dense.decomposition.chol | Ejml ( Efficient Java Matrix Library ) |
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EigenPowerMethod | The power method is an iterative method that can be used to find dominant eigen vector in a matrix. | Class | org.ejml.alg.dense.decomposition.eig | Ejml ( Efficient Java Matrix Library ) |
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EigenvalueExtractor | | Interface | org.ejml.alg.dense.decomposition.eig | Ejml ( Efficient Java Matrix Library ) |
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EigenvalueSmall | | Class | org.ejml.alg.dense.decomposition.eig | Ejml ( Efficient Java Matrix Library ) |
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HessenbergSimilarDecomposition_D64 | Finds the decomposition of a matrix in the form of: where A is an m by m matrix, O is an orthogonal matrix, and H is an upper Hessenberg matrix. | Class | org.ejml.alg.dense.decomposition.hessenberg | Ejml ( Efficient Java Matrix Library ) |
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LUDecompositionAlt_D64 | An LU decomposition algorithm that originally came from Jama. | Class | org.ejml.alg.dense.decomposition.lu | Ejml ( Efficient Java Matrix Library ) |
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LUDecompositionBase_D64 | Contains common data structures and operations for LU decomposition algorithms. | Class | org.ejml.alg.dense.decomposition.lu | Ejml ( Efficient Java Matrix Library ) |
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QRColPivDecompositionHouseholderColumn_D64 | Performs QR decomposition with column pivoting. | Class | org.ejml.alg.dense.decomposition.qr | Ejml ( Efficient Java Matrix Library ) |
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QRDecomposition_B64_to_D64 | Wrapper that allows QRDecomposition(BlockMatrix64F) to be used as a QRDecomposition(DenseMatrix64F). | Class | org.ejml.alg.dense.decomposition.qr | Ejml ( Efficient Java Matrix Library ) |
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QRDecompositionHouseholder_D64 | This variation of QR decomposition uses reflections to compute the Q matrix. | Class | org.ejml.alg.dense.decomposition.qr | Ejml ( Efficient Java Matrix Library ) |
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QRDecompositionHouseholderColumn_D64 | Householder QR decomposition is rich in operations along the columns of the matrix. | Class | org.ejml.alg.dense.decomposition.qr | Ejml ( Efficient Java Matrix Library ) |
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QRDecompositionHouseholderTran_D64 | Householder QR decomposition is rich in operations along the columns of the matrix. | Class | org.ejml.alg.dense.decomposition.qr | Ejml ( Efficient Java Matrix Library ) |
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QrHelperFunctions_D64 | Contains different functions that are useful for computing the QR decomposition of a matrix. | Class | org.ejml.alg.dense.decomposition.qr | Ejml ( Efficient Java Matrix Library ) |
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QrUpdate | The effects of adding and removing rows from the A matrix in a QR decomposition can be computed much faster than simply recomputing the whole decomposition. | Class | org.ejml.alg.dense.decomposition.qr | Ejml ( Efficient Java Matrix Library ) |
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SafeSvd | Wraps around a SingularValueDecomposition and ensures that the input is not modified. | Class | org.ejml.alg.dense.decomposition.svd | Ejml ( Efficient Java Matrix Library ) |
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SvdImplicitQrAlgorithm | Computes the QR decomposition of a bidiagonal matrix. | Class | org.ejml.alg.dense.decomposition.svd.implicitqr | Ejml ( Efficient Java Matrix Library ) |
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SvdImplicitQrDecompose_D64 | Computes the Singular value decomposition of a matrix using the implicit QR algorithm for singular value decomposition. | Class | org.ejml.alg.dense.decomposition.svd | Ejml ( Efficient Java Matrix Library ) |
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SwitchingEigenDecomposition | Checks to see what type of matrix is being decomposed and calls different eigenvalue decomposition algorithms depending on the results. | Class | org.ejml.alg.dense.decomposition.eig | Ejml ( Efficient Java Matrix Library ) |
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SymmetricQrAlgorithm | Computes the eigenvalues and eigenvectors of a symmetric tridiagonal matrix using the symmetric QR algorithm. | Class | org.ejml.alg.dense.decomposition.eig.symm | Ejml ( Efficient Java Matrix Library ) |
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SymmetricQRAlgorithmDecomposition_D64 | Computes the eigenvalues and eigenvectors of a real symmetric matrix using the symmetric implicit QR algorithm. | Class | org.ejml.alg.dense.decomposition.eig | Ejml ( Efficient Java Matrix Library ) |
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SymmetricQREigenHelper | A helper class for the symmetric matrix implicit QR algorithm for eigenvalue decomposition. | Class | org.ejml.alg.dense.decomposition.eig.symm | Ejml ( Efficient Java Matrix Library ) |
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TriangularSolver | This contains algorithms for solving systems of equations where T is a non-singular triangular matrix: | Class | org.ejml.alg.dense.decomposition | Ejml ( Efficient Java Matrix Library ) |
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TridiagonalDecomposition_B64_to_D64 | | Class | org.ejml.alg.dense.decomposition.hessenberg | Ejml ( Efficient Java Matrix Library ) |
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TridiagonalDecompositionHouseholder_D64 | Performs a similar tridiagonal decomposition on a square symmetric input matrix. | Class | org.ejml.alg.dense.decomposition.hessenberg | Ejml ( Efficient Java Matrix Library ) |
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TridiagonalDecompositionHouseholderOrig_D64 | A straight forward implementation from "Fundamentals of Matrix Computations," Second Edition. | Class | org.ejml.alg.dense.decomposition.hessenberg | Ejml ( Efficient Java Matrix Library ) |
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WatchedDoubleStepQRDecomposition_D64 | Finds the eigenvalue decomposition of an arbitrary square matrix using the implicit double-step QR algorithm. | Class | org.ejml.alg.dense.decomposition.eig | Ejml ( Efficient Java Matrix Library ) |
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WatchedDoubleStepQREigen | The double step implicit Eigenvalue decomposition algorithm is fairly complicated and needs to be designed so that it can handle several special cases. | Class | org.ejml.alg.dense.decomposition.eig.watched | Ejml ( Efficient Java Matrix Library ) |
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WatchedDoubleStepQREigenvalue | | Class | org.ejml.alg.dense.decomposition.eig.watched | Ejml ( Efficient Java Matrix Library ) |
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WatchedDoubleStepQREigenvector | | Class | org.ejml.alg.dense.decomposition.eig.watched | Ejml ( Efficient Java Matrix Library ) |