[EMAIL PROTECTED] (psu) wrote in message news:<[EMAIL PROTECTED]>... > Can it not be argued that if the noise structure is 'well known', for > example, we know for a fact that the noise is an uncorrelated white > noise process, then the 'optimal' filter for this particular signal > embedded in such a noise is simply the expectation of the process at any > time t? > > i.e., > > If we assume that Observations = Signal + Noise > > we can take expectations to obtain: > > E(obs) = E(sig) + E(noise) > > since E(noise) = 0 > > E(obs) = E(sig) > > So, taking expectations gives us the exact structure of the signal in > this case... > > so, is it reasonable then to say that more advanced filtering methods > are required only when the noise cannot be said to be a simple additive > white noise process, such as produced from measurement uncertainty? > > . >Yes ...
See http://www.autobox.com/outlier.html and in particular http://www.autobox.com/t1b3.html For a ton of "stuff" on time series/signal/outliers see http://www.autobox.com/teach.html .. For free software http://www.autobox.com/freef.exe Dave Reilly Automatic Forecasting Systems hrrp://www.autobox.com . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
