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## Re: Smooth line approximating minima of a data series

**From**: |
Olaf Till |

**Subject**: |
Re: Smooth line approximating minima of a data series |

**Date**: |
Wed, 24 Feb 2010 11:23:06 +0100 |

**User-agent**: |
Mutt/1.5.18 (2008-05-17) |

On Wed, Feb 24, 2010 at 09:04:07AM +0100, Matthias Brennwald wrote:
>* 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?*
What about polyfit?
Olaf