We have several large scale nonlinear system of equations H(z)=0. The dimensions are between 877-1045.
I obtained Jacobian and checked whether my Jacobian is true by:
options=optimset('Jacobian', 'on', 'DerivativeCheck', 'on','LargeScale', 'on');
fsolve('H', z, options)
maximum discrepancy between Jacobians is 1e-5
The Jacobian is a sparse matrix (for example it has 9496 nonzero elements for 940x940 dimension)
I tried to solve by:
%try with diagonal preconditioner:
fun=@H;
options = optimset('Display','iter','Algorithm','trust-region reflective','Jacobian','on','PrecondBandWidth',0);
[x,fval,exitflag,output] = fsolve(fun,z,options);
%try with a three diagonal preconditioner 'PrecondBandWidth',1
Cannot find the solutions:
optimality conditions: 0.00672 for 149. iteration and 0.00391 for 192 (in 15 minutes)
Do you have any suggestions for finding solutions to my large scale problems?