ASN Filter Designer’s ANSI C SDK framework, provides developers with a comprehensive C code framework for developing AIoT filtering application on microcontrollers and embedded platforms. Although the framework has been primarily designed to support the just ASN filter Designer’s filter cascade, it is possible to create extra filter objects to augment the cascade.

Two common filtering methods used by AIoT developers are the Median and moving average (MA) filters. Although these fully integrated within the Framework’s filter cascade, it is often useful to have the flexibility of an additional filtering block to act as a post filter smoothing filter.

An extra median or MA filter may be easily added to `main.c`

as shown below. Notice that data is filtered in blocks of 4 as required by the framework.

## Median filter

The Median filter is non-linear filtering method that uses the concept of majority voting (i.e. calculating the median) to remove glitches and smooth data. It is edge preserving, making it a good choice for enhancing square waves or pulse like data.

#include "ASN_DSP/DSPFilters/MedianFilter.h" float InputTemp[4]; float OutputTemp[4]; MedianFilter_t MyMedianfilter; InitMedianFilter(&MyMedianfilter,7); // median of length 7 for (n=0; n<TEST_LENGTH_SAMPLES; n+=4) { InputTemp[0]=InputValues[n]; InputTemp[1]=InputValues[n+1]; InputTemp[2]=InputValues[n+2]; InputTemp[3]=InputValues[n+3]; MedianFilterData(&MyMedianfilter,InputTemp, OutputTemp); OutputValues[n]=OutputTemp[0]; OutputValues[n+1]=OutputTemp[1]; OutputValues[n+2]=OutputTemp[2]; OutputValues[n+3]=OutputTemp[3]; }

## Moving Average filter

The moving average (MA) filter is optimal for reducing random noise while retaining a sharp step response, making it a versatile building block for smart sensor signal processing applications. It is perhaps one of the most widely used digital filters due to its conceptual simplicity and ease of implementation.

#include "ASN_DSP/DSPFilters/MAFilter.h" float InputTemp[4]; float OutputTemp[4]; MAFilter_t MyMAfilter; InitMAFilter(&MyMAfilter,9); // MA of length 9 for (n=0; n<TEST_LENGTH_SAMPLES; n+=4) { InputTemp[0]=InputValues[n]; InputTemp[1]=InputValues[n+1]; InputTemp[2]=InputValues[n+2]; InputTemp[3]=InputValues[n+3]; MAFilterData(&MyMAfilter,InputTemp, OutputTemp); OutputValues[n]=OutputTemp[0]; OutputValues[n+1]=OutputTemp[1]; OutputValues[n+2]=OutputTemp[2]; OutputValues[n+3]=OutputTemp[3]; }