Deploy Bandpass Filters Using the Wolfram Language

In this project I will analyze the responses of a bandpass Butterworth and Chebyshev1 filter deployed to an Arduino Nano from the Wolfram Language.

As these are analog filters, they need to be discretized before deployment. It is interesting to see in real-time how the frequency response of deployed filter closely matches that of the analog version.

The frequency responses create a mental imagery of what the real-time responses of the filters would look like and how they would differ from each other. But I wanted to make it concrete. So I created a visualization juxtaposing the frequency responses of the analog filters and the real-time responses of discretized filters, to see both in real-time as I change the parameters of the input signals.

In the first part, the filters are computed, analyzed, and deployed. In the second part, I acquire and analyze the filtered data to visualize the responses and evaluate the performance of the filters.

All the computations and tasks are done using the Wolfram Language: I use its signal processing capabilities to compute and analyze the filters, the Microcontroller Kit to deploy the filters, the device framework to do the data acquisition, and the notebook interface to visualize the data.

For the complete post please see this cloud notebook.