Moving average filter algorithm

1. How does the moving average filter work?
2. What is formula of average moving filter?
3. Which filter is moving average filter?
4. Is moving average a good filter?

How does the moving average filter work?

The moving average filter is a simple Low Pass FIR (Finite Impulse Response) filter commonly used for regulating an array of sampled data/signal. It takes M samples of input at a time and takes the average of those to produce a single output point.

What is formula of average moving filter?

The difference equation of an exponential moving average filter is very simple: y [ n ] = α x [ n ] + ( 1 − α ) y [ n − 1 ] In this equation, is the current output, y [ n − 1 ] is the previous output, and is the current input; is a number between 0 and 1.

Which filter is moving average filter?

The moving average filter is a special case of the regular FIR filter. Both filters have finite impulse responses. The moving average filter uses a sequence of scaled 1s as coefficients, while the FIR filter coefficients are designed based on the filter specifications. They are not usually a sequence of 1s.

Is moving average a good filter?

Not only is the moving average filter very good for many applications, it is optimal for a common problem, reducing random white noise while keeping the sharpest step response. FIGURE 15-1 Example of a moving average filter.