MATLAB Function Reference Volume 1: A - E - Bad Request

2cgs
Purpose Conjugate Gradients Squared method
Syntax x = cgs(A,b)
cgs(A,b,tol)
cgs(A,b,tol,maxit)
cgs(A,b,tol,maxit,M)
cgs(A,b,tol,maxit,M1,M2)
cgs(A,b,tol,maxit,M1,M2,x0)
cgs(afun,b,tol,maxit,m1fun,m2fun,x0,p1,p2,...)
[x,flag] = cgs(A,b,...)
[x,flag,relres] = cgs(A,b,...)
[x,flag,relres,iter] = cgs(A,b,...)
[x,flag,relres,iter,resvec] = cgs(A,b,...)
Description x = cgs(A,b) attempts to solve the system of linear equations A*x = b for x.
The n-by-n coefficient matrix A must be square and the column vector b must
have length n. A can be a function afun such that afun(x) returns A*x.
If cgs converges, a message to that effect is displayed. If cgs fails to converge
after the maximum number of iterations or halts for any reason, a warning
message is printed displaying the relative residual norm(b-A*x)/norm(b) and
the iteration number at which the method stopped or failed.
cgs(A,b,tol) specifies the tolerance of the method, tol. Iftol is [], then cgs
uses the default, 1e-6.
cgs(A,b,tol,maxit) specifies the maximum number of iterations, maxit. If
maxit is [] then cgs uses the default, min(n,20).
cgs(A,b,tol,maxit,M) and cgs(A,b,tol,maxit,M1,M2) use the
preconditioner M or M = M1*M2 and effectively solve the system
inv(M)*A*x = inv(M)*b for x. If M is [] then cgs applies no preconditioner. M
can be a function that returns M\x.
cgs(A,b,tol,maxit,M1,M2,x0) specifies the initial guess x0. If x0 is [], then
cgs uses the default, an all-zero vector.
cgs
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