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SuperLU is a general purpose library for the direct solution of large, sparse, nonsymmetric systems of linear equations on high performance machines. The library is written in C and is callable from either C or Fortran. The library routines will perform an LU decomposition with partial pivoting and triangular system solves through forward and back substitution. The LU factorization routines can handle non-square matrices but the triangular solves are performed only for square matrices. The matrix columns may be preordered (before factorization) either through library or user supplied routines. This preordering for sparsity is completely separate from the factorization. Working precision iterative refinement subroutines are provided for improved backward stability. Routines are also provided to equilibrate the system, estimate the condition number, calculate the relative backward error, and estimate error bounds for the refined solutions. -SuperLU is a general purpose library for the direct solution of large, sparse, nonsymmetric systems of linear equations on high performance machines. The library is written in C and is callable from either C or
Update : 2025-02-19 Size : 1.87mb Publisher : anfangde

Modify the Matlab Gauss Elimination routine given in lectures so that it (a) performs implicit complete pivoting, and (b) handles m right hand sides at once by performing an LU decomposition of the matrix A first and then doing forward substitution and back substitution (hence not modifying the right hand side as the elimination is perfomed). Test your program and then run it on the system AX = B-Modify the Matlab Gauss Elimination routine given in lectures so that it (a) performs implicit complete pivoting, and (b) handles m right hand sides at once by performing an LU decomposition of the matrix A first and then doing forward substitution and back substitution ( hence not modifying the right hand side as the elimination is perfomed). Test your program and then run it on the system AX = B
Update : 2025-02-19 Size : 1kb Publisher : liuzhenghao

DL : 0
Solving an upper triangular system U x = b by back-substitution Solving a lower triangular system L x = b by forward-substitution-backward substitution and forward substitution
Update : 2025-02-19 Size : 1kb Publisher : QuanyuZhao

配电网辐射状前推回代潮流计算程序,节点可以任意更改。-Forward and backward substitution flow calculation
Update : 2025-02-19 Size : 1kb Publisher : 小丁

Systems of linear equations Our Matlab function for naive Gaussian elimination looks like this: function x = naiv_gauss(A,b) n = length(b) x = zeros(n,1) for k=1:n-1 forward elimination for i=k+1:n xmult = A(i,k)/A(k,k) for j=k+1:n A(i,j) = A(i,j)-xmult*A(k,j) end b(i) = b(i)-xmult*b(k) end end back substitution x(n) = b(n)/A(n,n) for i=n-1:-1:1 sum = b(i) for j=i+1:n sum = sum-A(i,j)*x(j) end x(i) = sum/A(i,i) end-Systems of linear equations Our Matlab function for naive Gaussian elimination looks like this: function x = naiv_gauss(A,b) n = length(b) x = zeros(n,1) for k=1:n-1 forward elimination for i=k+1:n xmult = A(i,k)/A(k,k) for j=k+1:n A(i,j) = A(i,j)-xmult*A(k,j) end b(i) = b(i)-xmult*b(k) end end back substitution x(n) = b(n)/A(n,n) for i=n-1:-1:1 sum = b(i) for j=i+1:n sum = sum-A(i,j)*x(j) end x(i) = sum/A(i,i) end
Update : 2025-02-19 Size : 37kb Publisher : amine

DL : 0
numerical algorithms , Cramer code ,Gaussian Elimination, lagrange interpolating, polynomials, Decomposition ,Forward substitution ,Back substitution
Update : 2025-02-19 Size : 1.08mb Publisher : maiso
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