Filter Design

Variations on the Moving Average

Figure 2. Impulse (left), step (middle), and frequency (right) responses for the triangular window.

The moving-average filter is a strong performer in the time domain, but not in the frequency domain. For those cases where you have to work with data for which both domains are important, there are “weighted” versions of the moving average that are… read more

Submitted on 1 February 2016

The Moving Average as a Filter

Figure 1. Smoothing with a moving average filter.

The moving average is often used for smoothing data in the presence of noise. The simple moving average is not always recognized as the Finite Impulse Response (FIR) filter that it is, while it is actually one of the most common filters in signal processing. Treating it as a filter allows… read more

Submitted on 4 December 2015