>> help fminsearch

 FMINSEARCH Multidimensional unconstrained nonlinear minimization (Nelder-Mead).
    X = FMINSEARCH(FUN,X0) starts at X0 and finds a local minimizer X of the
    function FUN. FUN accepts input X and returns a scalar function value 
    F evaluated at X. X0 can be a scalar, vector or matrix. 
 
    X = FMINSEARCH(FUN,X0,OPTIONS)  minimizes with the default optimization
    parameters replaced by values in the structure OPTIONS, created
    with the OPTIMSET function.  See OPTIMSET for details.  FMINSEARCH uses
    these options: Display, TolX, TolFun, MaxFunEvals, and MaxIter. 
 
    X = FMINSEARCH(FUN,X0,OPTIONS,P1,P2,...) provides for additional
    arguments which are passed to the objective function, F=feval(FUN,X,P1,P2,...).
    Pass an empty matrix for OPTIONS to use the default values.
    (Use OPTIONS = [] as a place holder if no options are set.)
 
    [X,FVAL]= FMINSEARCH(...) returns the value of the objective function,
    described in FUN, at X.
 
    [X,FVAL,EXITFLAG] = FMINSEARCH(...) returns a string EXITFLAG that 
    describes the exit condition of FMINSEARCH.  
    If EXITFLAG is:
      1 then FMINSEARCH converged with a solution X.
      0 then the maximum number of iterations was reached.
    
    [X,FVAL,EXITFLAG,OUTPUT] = FMINSEARCH(...) returns a structure
    OUTPUT with the number of iterations taken in OUTPUT.iterations.
 
    Examples
      FUN can be specified using @:
         X = fminsearch(@sin,3)
      finds a minimum of the SIN function near 3.
      In this case, SIN is a function that returns a scalar function value 
      SIN evaluated at X.
 
      FUN can also be an inline object:
         X = fminsearch(inline('norm(x)'),[1;2;3])
      returns a minimum near [0;0;0].
 
    FMINSEARCH uses the Nelder-Mead simplex (direct search) method.
 
    See also OPTIMSET, FMINBND, @, INLINE.