Computes the filter coefficients for all Savitzky-Golay smoothing filters.
sgolay(p, n, m = 0, ts = 1)
filter order.
filter length (must be odd).
return the m-th derivative of the filter coefficients.
time scaling factor.
An square matrix with dimensions length(n)
that is of
class 'sgolayFilter'
(so it can be used with filter
).
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.
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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