Here is one way to get multiple minima: call NMinimize multiple times with different random seeds, which will cause different optimization paths to be taken. This defines a ...
Complement[e_all, e_1, e_2, ...] gives the elements in e_all which are not in any of the e_i.
TimeUsed[] gives the total number of seconds of CPU time used so far in the current Mathematica session.
NIntegrate[f, {x, x_min, x_max}] gives a numerical approximation to the integral \[Integral]_x_min^x_max\ f\ d \ x. NIntegrate[f, {x, x_min, x_max}, {y, y_min, y_max}, ...] ...
PolarPlot[r, {\[Theta], \[Theta]_min, \[Theta]_max}] generates a polar plot of a curve with radius r as a function of angle \[Theta].PolarPlot[{f_1, f_2, ...}, {\[Theta], ...
NMaximize[f, x] maximizes f numerically with respect to x.NMaximize[f, {x, y, ...}] maximizes f numerically with respect to x, y, .... NMaximize[{f, cons}, {x, y, ...}] ...
NMinimize[f, x] minimizes f numerically with respect to x.NMinimize[f, {x, y, ...}] minimizes f numerically with respect to x, y, .... NMinimize[{f, cons}, {x, y, ...}] ...
Newton's method for nonlinear equations is based on a linear approximation so the Newton step is found simply by setting M_k(p)=0, Near a root of the equations, Newton's ...
ListPlot[{y_1, y_2, ...}] plots points corresponding to a list of values, assumed to correspond to x coordinates 1, 2, .... ListPlot[{{x_1, y_1}, {x_2, y_2}, ...}] plots a ...
Mathematica allows you to customize your 2D and 3D graphics through a variety of options.