Since creating a filter design would be a very smal portion of my job activities, I would need to find some source of the design, either published or for sale. So presentations like this do wind up being a very useful resource on many occasions.
I didn't know that performing an FFT on the filter coefficients would produce the same characteristic as the filter. That is interesting. I have always used software to produce the coefficients, and somewhat trusted the output. I do usually verify the overall gain by summing the coefficients, however.
It seems that the FFT output produced by 65 coefficients of 0.015625 is skewed by the zero padding. I would expect the FFT of a constant value to have all energy content to appear in the 0Hz bin, and absolutely nothing in the other frequency bins. By padding it out to 128 points with zeroes, you have essentially created a square wave with approximately a 50% duty cycle, and the FFT result looks like it (the odd harmonic content).
Switched-capacitor filters have a few disadvantages. They exhibit greater sensitivity to noise than their op-amp-based filter siblings, and they have low-amplitude clock-signal artifacts -- clock feedthrough -- on their outputs.
For industrial control applications, or even a simple assembly line, that machine can go almost 24/7 without a break. But what happens when the task is a little more complex? That’s where the “smart” machine would come in. The smart machine is one that has some simple (or complex in some cases) processing capability to be able to adapt to changing conditions. Such machines are suited for a host of applications, including automotive, aerospace, defense, medical, computers and electronics, telecommunications, consumer goods, and so on. This discussion will examine what’s possible with smart machines, and what tradeoffs need to be made to implement such a solution.