Abstract
In many applications one is measuring a variable that is both slowly varying and also corrupted by random noise. Then it is often desirable to apply a smoothing filter to the measured data in order to reconstruct the underlying smooth function. We may assume that the noise is independent of the observed variable. Furthermore we assume that the noise obeys a normal distribution with mean zero and standard deviation δ.
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© 1997 Springer-Verlag Berlin Heidelberg
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Gander, W., von Matt, U. (1997). Smoothing Filters. In: Solving Problems in Scientific Computing Using Maple and MATLAB®. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-97953-8_9
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DOI: https://doi.org/10.1007/978-3-642-97953-8_9
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