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? . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
