Skip to content
LearnStatisticspowered by UpThink

Statistics and data science, defined

Recursive Filter

In recursive filters, the output at the moment is a function of the output values mathematical symbol at the previous moments and, probably, of the input values.

A major advantage of recursive filters over nonrecursivefilters is that they are computationally simpler. For example, for any recursive linear filter, there is a functionally equivalent non-recursive linear filter. But the non-recursive variant may be characterized by an infinitely large window size and, hence, be difficult for practical implementation. (See, for example, explanations on the exponential filter).

Mathematically, a recursive filter may be described by the following general expression:

Formula: Recursive Filter

where

  • mathematical symbol is an arbitrary function of the previous output values and input values , linear or nonlinear.

Some examples of recursive filters are the exponential filter, the Kalman filter.

Related entries

Where this gets used

We teach data science and statistics online, one subject at a time, on fixed start dates with an instructor who marks your work.