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#Com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse Classes and Interfaces - 38 results found.
| Name | Description | Type | Package | Framework |
| BiconjugateGradientSolver | The Biconjugate Gradient method (BiCG) is useful for solving non-symmetric n-by-n linear systems. | Class | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse.solver.iterative.nonstationary | SuanShu |
| BiconjugateGradientStabilizedSolver | The Biconjugate Gradient Stabilized (BiCGSTAB) method is useful for solving non-symmetric n-by-n linear systems. | Class | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse.solver.iterative.nonstationary | SuanShu |
| ConjugateGradientNormalErrorSolver | For an under-determined system of linear equations, Ax = b, or when the coefficient matrix A is non-symmetric and nonsingular, | Class | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse.solver.iterative.nonstationary | SuanShu |
| ConjugateGradientNormalResidualSolver | For an under-determined system of linear equations, Ax = b, or when the coefficient matrix A is non-symmetric and nonsingular, | Class | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse.solver.iterative.nonstationary | SuanShu |
| ConjugateGradientSolver | The Conjugate Gradient method (CG) is useful for solving a symmetric n-by-n linear system. | Class | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse.solver.iterative.nonstationary | SuanShu |
| ConjugateGradientSquaredSolver | The Conjugate Gradient Squared method (CGS) is useful for solving a non-symmetric n-by-n linear system. | Class | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse.solver.iterative.nonstationary | SuanShu |
| ConvergenceFailure | This exception is thrown by IterativeLinearSystemSolver. | Class | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse.solver.iterative | SuanShu |
| ConvergenceFailure .Reason | the reasons for the convergence failureThrown when the iterative algorithm fails to proceed during its | Class | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse.solver.iterative | SuanShu |
| CSRSparseMatrix | The Compressed Sparse Row (CSR) format for sparse matrix has this representation: (value, col_ind, row_ptr). | Class | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse | SuanShu |
| DOKSparseMatrix | The Dictionary Of Key (DOK) format for sparse matrix uses the coordinates of non-zero entries in the matrix as keys. | Class | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse | SuanShu |
| GaussSeidelSolver | Similar to the Jacobi method, the Gauss-Seidel method (GS) solves each equation in sequential order. | Class | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse.solver.iterative.stationary | SuanShu |
| GeneralizedConjugateResidualSolver | The Generalized Conjugate Residual method (GCR) is useful for solving a non-symmetric n-by-n linear system. | Class | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse.solver.iterative.nonstationary | SuanShu |
| GeneralizedMinimalResidualSolver | The Generalized Minimal Residual method (GMRES) is useful for solving a non-symmetric n-by-n linear system. | Class | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse.solver.iterative.nonstationary | SuanShu |
| IdentityPreconditioner | This identity preconditioner is used when no preconditioning is applied. | Class | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse.solver.iterative.preconditioner | SuanShu |
| IterativeLinearSystemSolver | An iterative method for solving an N-by-N (or non-square) linear system Ax = b involves a sequence of matrix-vector multiplications. | Interface | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse.solver.iterative | SuanShu |
| IterativeLinearSystemSolver .Solution | This is the solution to a system of linear equations using an iterativeSearch for a solution that optimizes the objective function from the | Interface | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse.solver.iterative | SuanShu |
| JacobiPreconditioner | The Jacobi (or diagonal) preconditioner is one of the simplest forms of preconditioning, such that the preconditioner is the diagonal of | Class | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse.solver.iterative.preconditioner | SuanShu |
| JacobiSolver | The Jacobi method solves sequentially n equations in a linear system Ax = b in isolation in each iteration. | Class | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse.solver.iterative.stationary | SuanShu |
| LILSparseMatrix | The list of lists (LIL) format for sparse matrix stores one list per row, where each entry stores a column index and value. | Class | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse | SuanShu |
| MatrixCoordinate | The location of a matrix entry is specified by a 2D coordinates (i, j), where i and j are the row-index and column-index of the entry respectively. | Class | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse | SuanShu |
| MinimalResidualSolver | The Minimal Residual method (MINRES) is useful for solving a symmetric n-by-n linear system (possibly indefinite or singular). | Class | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse.solver.iterative.nonstationary | SuanShu |
| Preconditioner | Preconditioning reduces the condition number of the coefficient matrix of a linear system to accelerate the convergence | Interface | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse.solver.iterative.preconditioner | SuanShu |
| PreconditionerFactory | This constructs a new instance of Preconditioner for a coefficient matrix. | Interface | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse.solver.iterative.preconditioner | SuanShu |
| QuasiMinimalResidualSolver | The Quasi-Minimal Residual method (QMR) is useful for solving a non-symmetric n-by-n linear system. | Class | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse.solver.iterative.nonstationary | SuanShu |
| SORSweep | This is a building block for to perform the forward or backward sweep. | Class | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse.solver.iterative.stationary | SuanShu |
| SparseMatrix | A sparse matrix stores only non-zero values. | Interface | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse | SuanShu |
| SparseMatrix .Entry | This is a (non-zero) entry in a sparse matrix. | Class | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse | SuanShu |
| SparseMatrix .Entry .TopLeftFirstComparator | This Comparator sorts the matrix coordinates first from top to bottom (rows), and then from left to right (columns). | Class | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse | SuanShu |
| SparseMatrixUtils | These are the utility functions for SparseMatrix. | Class | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse | SuanShu |
| SparseStructure | This interface defines common operations on sparse structures such as sparse vector or sparse matrix. | Interface | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse | SuanShu |
| SparseVector | A sparse vector stores only non-zero values. | Class | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse | SuanShu |
| SparseVector .Entry | This is an entry in a SparseVector. | Class | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse | SuanShu |
| SparseVector .Entry .Comparator | This Comparator sorts the matrix coordinates first from top to bottom (rows), and then from left to right (columns). | Class | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse | SuanShu |
| SparseVector .Iterator | This wrapper class overrides the Iterator. | Class | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse | SuanShu |
| SSORPreconditioner | SSOR preconditioner is derived from a symmetric coefficient matrix A which is decomposed as | Class | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse.solver.iterative.preconditioner | SuanShu |
| SteepestDescentSolver | The Steepest Descent method (SDM) solves a symmetric n-by-n linear system. | Class | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse.solver.iterative.nonstationary | SuanShu |
| SuccessiveOverrelaxationSolver | The Successive Overrelaxation method (SOR), is devised by applying extrapolation to the Gauss-Seidel method. | Class | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse.solver.iterative.stationary | SuanShu |
| SymmetricSuccessiveOverrelaxationSolver | The Symmetric Successive Overrelaxation method (SSOR) is like SOR, but it performs in each | Class | com.numericalmethod.suanshu.algebra.linear.matrix.doubles.matrixtype.sparse.solver.iterative.stationary | SuanShu |