  The classical Maximum Entropy (ME) problem consists of determining a
probability distribution function (pdf) from a finite set of expectations of
known functions. The solution depends on $N+1$ Lagrange multipliers which are
determined by solving the set of nonlinear equations formed by the $N$ data
constraints and the normalization constraint. In this short communication we
give three Matlab programs to calculate these Lagrange multipliers. The first
considers the general case where the functions can be any functions. The second
considers the special case of power functions $x^n$. In this case the data are
the geometrical moments of $p(x)$. The third considers the special case of
Fourier series functions $\exp(-j n \omega x)$. In this case the data are the
trigonometrical moments of $p(x)$. Some examples are also given to illustrate
the usefullness of these programs.
