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== The confusion in terms and the relation between Filtering and Smoothing problems==
Smoothing (estimation) and smoothing (convolution) can mean totally different, but sound like they are apparently similar. The concepts are different and are used in different historical contexts. The '''requirements''' are very different.
Both the smoothing problem (in sense of estimation) and the filtering problem (in sense of estimation) are often confused with smoothing and filtering in other contexts (especially non-stochastic signal processing, often a name of various types of convolution). These names are used in the context of World War 2 defined by people like [[Norbert Wiener]] <ref name="wiener-report"/><ref name="wiener-book" />. They are distinct in the following two senses:
1. Convolution: The smoothing in the sense of '''convolution''' (eg, moving average, low-pass filtering, convolution with a kernel, or blurring using Laplace filters in [[image processing]]) is simpler. Especially non-stochastic and non-Bayesian signal processing, without any hidden variables.
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