Unconstrained minimizer fminunc in MATLAB

The routine fminunc, part of the optional MATLAB optimization toolkit, uses either a gradient or a Newton algorithm to solve an unconstrained, continuous optimization problem, with the choice of method depending upon the size of the problem and upon the level of information about the gradient and Hessian provided by the user. It is called with the syntax 

The output arguments include the local minimum x and its cost function value F. 

We demonstrate fminunc for the simple cost function (5.15) used to compare the performance of the steepest descent and conjugate gradient methods. The routine sim-ple.cost.func.m that returns the value of this cost function was presented previously following (5.15). The code below uses fminunc to find the minimum at (1,2), 

Warning Gradient must be provided for trust-region method  

Optimization terminated relative infinity-norm of gradient less than options.TolFun. x=l 2 F=0 

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