Quadratic Optimization using Newtons Method
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I am writing Newtons method to solve an optimization problem. I have written the following code:
function estimate = newtonMethod(f,df,x0,tolerance) %f & df are functions that contain OP & gradient respectively, x0 is initial guess, tolerance is 1e-12
estimate = x0; % Initial guess
iterations = 40; % Maximum number of iterations
for j = 1:iterations;
dx = f(estimate) / df(estimate)';
estimate = estimate - dx';
% Stop criterion:
if abs(dx) < tolerance
return
end
end
end
However, the vector 'u' doesn't seem to be a good solution. My question is: Is this the correct way of solving this OP using Newtons Method? I would highly appreciate suggestions on this.
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