savitzky golay smoothing filter c

The weights are given by the tricube function shown below. Each subset of the data set is fit with a straight horizontal line as opposed to a higher order polynomial. The data is very noisy and the peak widths vary from broad to narrow. The local regression smoothing process follows these steps for each data point:. Output Arguments collapse all y — Filtered signal vector matrix.

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