Smooth line approximating minima of a data series

[Matthias Brennwald]

Dear all

Consider a series of data values that reflect a smooth function (e.g.  
a low-degree polynomial), but there might be additional features in  
the data (e.g. narrow peaks or noise). I'd like to fit a polynomial to  
this data, whereby this polynomial reflects a smooth approximation of  
the minima of the raw data (I call this the "base line"). The  
following might help to illustrate what I'm trying to accomplish:

    x = [-1:0.01:1]; % x-axis values
    p = [-3 2 1 0]; yp = polyval (p,x); % make up a polynomial  
reflecting the "base line" for illustration
    y = yp + rand(size(x)); % this would be the raw data
    plot (x,y,x,yp); legend ('raw data','base line') % plot the raw  
data and the polynomial for illustration

Has anyone an idea of how to accomplish this? Are there standard  
methods? I'd appreciate any hints.

Thanks
Matthias