Optimization problem using Quasi Newton method

Given x_t and c_mn, the objective function is defined as:
I am trying to solve the above objective function for theta using quasi newton method. But there seem to be some problem with my code as it's not working. Could somebody please help me with this?
Following is my matlab code:
Code for defining objective function:
function f = objfuntc(x_t,c_mn,theta )
L = length(x_t );
[M,N] =size(c_mn);
f = 0 ;
for t = 1:L
xs = 0 ;
for n = 1:N
for m=1:M
xs = xs + c_mn(m,n)*exp(1i*2*pi*m*(t - n -2) + theta);
end
end
f = f + (x_t(t) - xs)^2 ;
end
Code for calling objective function:
x_t = rand(16,1 );
L = length(x_t);
a = 1;
M = L;
c = rand(M*L/a,1 );
c_mn=reshape(c,[M,L/a]);
J = @(theta) objfuntc(x_t,c_mn,theta )
theta0 = 10 ;
options = optimoptions('fminunc','Algorithm','quasi-newton ');
[theta, thetaval] = fminunc(J,theta0,options)

12 comentarios

John D'Errico
John D'Errico el 24 de Jun. de 2018
Why do you want to write your own optimizer in MATLAB? That is generally a bad idea, when optimization tools written by professionals are readily available.
christina
christina el 24 de Jun. de 2018
I am using MATLABs fminunc. But my problem is, I can't seem to run the code.
Torsten
Torsten el 25 de Jun. de 2018
The variable you want to return from "objfun" is called "J", not "f".
christina
christina el 25 de Jun. de 2018
Ahh, sorry that was a typo here. I still have the same problem.
Torsten
Torsten el 25 de Jun. de 2018
J = @(theta) objfun(x_t,c_mn,theta )
instead of
J = @(theta) objfuntc(x_t,c_mn,theta )
christina
christina el 25 de Jun. de 2018
Still not fixed.
Torsten
Torsten el 25 de Jun. de 2018
Editada: Torsten el 25 de Jun. de 2018
Put this code in one file, name it "main.m", open it in MATLAB and run it.
function main
x_t = rand(16,1 );
L = length(x_t);
a = 1;
M = L;
c = rand(M*L/a,1 );
c_mn=reshape(c,[M,L/a]);
J = @(theta) objfuntc(x_t,c_mn,theta )
theta0 = 10 ;
options = optimoptions('fminunc','Algorithm','quasi-newton ');
[theta, thetaval] = fminunc(J,theta0,options)
end
function f = objfuntc(x_t,c_mn,theta )
L = length(x_t );
[M,N] =size(c_mn);
f = 0 ;
for t = 1:L
xs = 0 ;
for n = 1:N
for m=1:M
xs = xs + c_mn(m,n)*sin(2*pi*m*(t - n -2) + theta);
end
end
f = f + (x_t(t) - xs)^2 ;
end
end
Many thanks, that worked! But if I slightly change the objective function, it shows some error again. I don't understand why. Could you please help me with this?
function main
x_t = rand(16,1 );
L = length(x_t );
a = 1 ;
M = L ;
c = rand(M*L/a,1 );
c_mn=reshape(c,[M,L/a ]);
J = @(theta) objfuntc(x_t,c_mn,theta )
theta0 = 10 ;
options = optimoptions('fminunc','Algorithm','quasi-newton ');
[theta, thetaval] = fminunc(J,theta0,options )
end
function f = objfuntc(x_t,c_mn,theta )
L = length(x_t );
[M,N] =size(c_mn );
f = 0 ;
for t = 1:L
xs = 0 ;
for n = 1:N
for m=1:M
% xs = xs + c_mn(m,n)*sin(2*pi*m*(t - n -2) + theta );
xs = xs + c_mn(m,n)*exp(1i*2*pi*m*(t - n -2) + theta );
end
end
f = f + (x_t(t) - xs)^2 ;
end
end
Torsten
Torsten el 25 de Jun. de 2018
Editada: Torsten el 25 de Jun. de 2018
x_t and c_mn can be complex-valued ?
You will have to use
f = f + (x_t(t) - xs)*conj(x_t(t) - xs) ;
instead of
f = f + (x_t(t) - xs)^2 ;
Best wishes
Torsten.
christina
christina el 25 de Jun. de 2018
It can be complex-valued.
Torsten
Torsten el 25 de Jun. de 2018
I complemented my comment.
christina
christina el 25 de Jun. de 2018
Thank you so much! That fixed everything.

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el 24 de Jun. de 2018

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el 25 de Jun. de 2018

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