How to identify stable deltas in a noisy signal This is a problem I have had to deal with in several different contexts now.  Given a real time signal which you expect to act as a noisy step function (periods of stability separated by quick changes in magnitude).  How does one identify when the signal has stabilized?  The tension in this problem is between identifying stability as fast as possible and reporting a new stable value with as much accuracy as possible.  

My solutions have varied depending on which of those I felt was more important and on how good my transition model was.  I have taken to calling this the stable deltas problem but have been unable to find any references on how to approach it.  Is this a studied problem in signal processing?  Does it have a name?
This sounds like the "change detection" problem of Basseville and Nikiforov, with the parameter after the change unknown (see section 2.4) of the linked PDF.

See, for instance, example 2.4.3:



The usual algorithm for dealing with this, and the one analyzed in the above-linked book is the CUSUM (Cumulative Sum) algorithm.