Savitzky-Golay smoothing filters
Computes the filter coefficients for all Savitzky-Golay smoothing filters.
sgolay(p, n, m = 0, ts = 1)
p |
filter order. |
n |
filter length (must be odd). |
m |
return the m-th derivative of the filter coefficients. |
ts |
time scaling factor. |
The early rows of the result F smooth based on future values and later rows
smooth based on past values, with the middle row using half future
and half past. In particular, you can use row i to estimate x[k]
based on the i-1 preceding values and the n-i following values of x
values as y[k] = F[i,] * x[(k-i+1):(k+n-i)].
Normally, you would apply the first (n-1)/2 rows to the first k
points of the vector, the last k rows to the last k points of the
vector and middle row to the remainder, but for example if you were
running on a realtime system where you wanted to smooth based on the
all the data collected up to the current time, with a lag of five
samples, you could apply just the filter on row n-5 to your window
of length n each time you added a new sample.
An square matrix with dimensions length(n) that is of
class 'sgolayFilter' (so it can be used with filter).
Original Octave version by Paul Kienzle pkienzle@users.sf.net. Modified by Pascal Dupuis. Conversion to R by Tom Short.
William H. Press, Saul A. Teukolsky, William T. Vetterling, Brian P. Flannery, Numerical Recipes in C: The Art of Scientific Computing , 2nd edition, Cambridge Univ. Press, N.Y., 1992.
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