#Moving average matlab 2008 code

Whereas, the filter function gives the output that is of same length as that of the input. The conv function gives the result of complete convolution and the length of the result is length(x)+ L -1. There exists a difference between using conv function and filter function for implementing an FIR filter.

#Moving average matlab 2008 code

When using conv function to implement the moving average filter, the following code can be used L = 5 The numerator coefficients for the moving average filter can be conveniently expressed in short notion as shown below L = 5 Therefore, the -point moving average filter can be coded as B = %numerator coefficients We can note from the difference equation and transfer function of the -point moving average filter, that following values for the numerator coefficients and denominator coefficients. Y = filter(B,A,x) %filter input x and get result in y Where, and are the filter coefficients and the order of the filter is the maximum of andР”Р‡or implementing equation (6) using the filter function, the Matlab function is called as B = %numerator coefficientsР”Р„ = %denominator coefficients In general, the Z-transform of a discrete-time filterРІР‚в„ўs output is related to the Z-transform of the input by

In Matlab, we can use the filter function or conv (convolution) to implement the moving average FIR filter. Simulating the filter in Matlab and Python The transfer function describes the input-output relationship of the system and for the -point Moving Average filter, the transfer function is given by Similarly, the Z-transform of the generic -sample Moving Average filter of equation (1) is By applying this idea, we can find the Z-transform of the -point moving average filter in equation (2) as In signal processing, delaying a signal by sample period (unit delay) is equivalent to multiplying the Z-transform by. If each discrete value of the input is represented as a -bit signal line from ADC (analog to digital converter), then we would require 4 sets of 12-Flip flops to implement the -point moving average filter shown in Figure 1.

Using D-Flip flop shift registers for digital hardware implementation.

Representing the input samples as an array in the computer memory and processing them.

The unit delay shown in Figure 1 is realized by either of the two options: This operation is represented as shown in the Figure 1 with the following difference equation for the input output relationship in discrete-time.Р”Р‡igure 1: Discrete-time 5-point Moving Average FIR filter The difference equation for a -point discrete-time moving average filter with input represented by the vector and the averaged output vector, isР”Р‡or example, a -point Moving Average FIR filter takes the current and previous four samples of input and calculates the average.

The MA filter performs three important functions:Р”РЋ) It takes input points, computes the average of those -points and produces a single output pointР”Сћ) Due to the computation/calculations involved, the filter introduces a definite amount of delayР”Р€) The filter acts as a Low Pass Filter (with poor frequency domain response and a good time domain response).

This implies that this filter has excellent time domain response but a poor frequency response. It is a very simple LPF (Low Pass Filter) structure that comes handy for scientists and engineers to filter unwanted noisy component from the intended data.Р”Р„s the filter length increases (the parameter ) the smoothness of the output increases, whereas the sharp transitions in the data are made increasingly blunt. It takes samples of input at a time and takes the average of those -samples and produces a single output point. The moving average filter is a simple Low Pass FIR (Finite Impulse Response) filter commonly used for smoothing an array of sampled data/signal.