Are noncausal filters ever used in practice? Basically what it says in the title; I have just started reading about these things and find noncausal filters pretty interesting in concept, but also they do not seem like they would have any advantage worth sacrificing real-time processing. Since "I have just started reading about these things" I feel as if I should make sure, and would also be interested in hearing: does anyone know if there are noncausal filters commonly used in practice? Why are they preferred? Thanks. 

Jeff Boucher.
Yes.

The problem with a system that operates in (near) real time is that you can't look into the future. One way you can deal with this is if you only need a finite amount of look-ahead is to put some delays and then delay the output so you're still causal.

However, many filtering problems have non-causality allowed, e.g. filtering a file on a disk (which occurs a lot. Audio or image or video files you download, time series such as finance data, or histories of systems). For example, you can collect a time series and smooth it with the rauch-tung-striebel filter rather than running a fixed lag smoother.