# fminsearch

Find the unconstrained minimum of a real function using the Nelder-Mead simplex algorithm.

## Syntax

x = fminsearch(@func,x0)

x = fminsearch(@func,x0,options)

[x,fval,info,output] = fminsearch(...)

## Inputs

func
The function to minimize.
x0
An estimate of the location of the minimum.
options
A struct containing option settings.
See optimset for details.

## Outputs

x
The location of the function minimum.
fval
The minimum of the function.
info
The convergence status flag.
info = 1
Function value converged to within tolX.
info = 0
Reached maximum number of iterations or function calls.
output
A struct containing iteration details. The members are as follows:
iterations
The number of iterations.
nfev
The number of function evaluations.
xiter
The candidate solution at each iteration.
fvaliter
The objective function value at each iteration.

## Examples

Minimize the Rosenbrock function.
``````function obj = Rosenbrock(x)
obj = (1 - x(1))^2 + 100 * (x(2) - x(1)^2)^2;
end

x0 = [-1.2, 1.0];
[x,fval] = fminsearch(@Rosenbrock, x0)``````
``````x = [Matrix] 1 x 2
1.00000  1.00000
fval = 5.29978e-14``````
Modify the previous example to pass an extra parameter to the function using a function handle.
``````function obj = Rosenbrock2(x, offset)
obj = (1 - x(1))^2 + 100 * (x(2) - x(1)^2)^2 + offset;
end

handle = @(x) Rosenbrock2(x, 2);
[x,fval] = fminsearch(handle, interval)``````
``````x = [Matrix] 1 x 2
1.00000  1.00000
fval = 2``````