Find minimum of unconstrained multivariable function using derivative-free method

Nonlinear programming solver. Searches for the minimum of a problem specified by

$$\underset{x}{\mathrm{min}}f(x)$$

*f*(*x*) is a function that returns a scalar, and
*x* is a vector or a matrix.

`x = fminsearch(fun,x0)`

`x = fminsearch(fun,x0,options)`

`x = fminsearch(problem)`

```
[x,fval]
= fminsearch(___)
```

```
[x,fval,exitflag]
= fminsearch(___)
```

```
[x,fval,exitflag,output]
= fminsearch(___)
```

`fminsearch`

only minimizes over the real numbers, that is, the vector or array*x*must only consist of real numbers and*f*(*x*) must only return real numbers. When*x*has complex values, split*x*into real and imaginary parts.Use

`fminsearch`

to solve nondifferentiable problems or problems with discontinuities, particularly if no discontinuity occurs near the solution.

`fminsearch`

uses the simplex search method
of Lagarias et al. [1]. This is a direct search method that does not use numerical
or analytic gradients as in `fminunc`

.
The algorithm is described in detail in fminsearch Algorithm.
The algorithm is not guaranteed to converge to a local minimum.

[1] Lagarias, J. C., J. A. Reeds, M. H. Wright,
and P. E. Wright. “Convergence Properties of the Nelder-Mead
Simplex Method in Low Dimensions.” *SIAM Journal
of Optimization*. Vol. 9, Number 1, 1998, pp. 112–147.