Conjugate gradient solver.

DESCRIPTION:

Solves a linear system of equation A(x)=b where A is a function corresponding to a symmetric positive definite matrix.

USAGE:

cg.solve(A, b, cg.max.iter=length(b), rel.conv=0.1, verbose=F, ...) 

REQUIRED ARGUMENTS:

A
function corresponding to a real n by n symmetric positive definite matrix operator. Example: wavelet tranform such as nd.dwt.
b
numeric vector.
cg.max.iter
real number giving the upper bound on the number of iterations.
rel.conv
real number giving the convergence threshold.
verbose
logical flag indicating whether or not information should be printed on the screen at each iteration.
...
additional argument used by the A() function. Example: wavelet or n.levels for wavelet tranforms.

VALUE:

numeric vector. Solution to A(x)=b.

REFERENCES:

Golub, G.H. and Van Loan, C.F. (1996). Matrix Computations. Johns Hopkins University Press, Baltimore, MD.

SEE ALSO:

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