kac | R Documentation |
Implements Kaczmarz's algorithm to solve a system of equations iteratively
kac(A, b, tolx, maxiter)
A |
Constraint matrix |
b |
right hand side |
tolx |
difference tolerence for successive iterations (stopping criteria) |
maxiter |
maximum iterations (stopping criteria) |
x |
solution |
Jonathan M. Lees<jonathan.lees@unc.edu>
Aster, R.C., C.H. Thurber, and B. Borchers, Parameter Estimation and Inverse Problems, Elsevier Academic Press, Amsterdam, 2005.
set.seed(2015)
G = setDesignG()
### % Setup the true model.
mtruem=matrix(rep(0, 16*16), ncol=16,nrow=16);
mtruem[9,9]=1; mtruem[9,10]=1; mtruem[9,11]=1;
mtruem[10,9]=1; mtruem[10,11]=1;
mtruem[11,9]=1; mtruem[11,10]=1; mtruem[11,11]=1;
mtruem[2,3]=1; mtruem[2,4]=1;
mtruem[3,3]=1; mtruem[3,4]=1;
### % reshape the true model to be a vector
mtruev=as.vector(mtruem);
### % Compute the data.
dtrue=G %*% mtruev;
### % Add the noise.
d=dtrue+0.1*rnorm(length(dtrue));
mkac<-kac(G,d,0.0,200)
par(mfrow=c(1,2))
imagesc(matrix(mtruem,16,16) , asp=1 , main="True Model" );
imagesc(matrix(mkac,16,16) , asp=1 , main="Kacz Solution" );
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