Quote:
Originally Posted by Tom Line
Chris, now you've got me really really curious. How are you filtering?
The only filtering I'm used to is floating average with X number of samples. However, that introduces significant lag. Are you using something more exotic?
I've read up on IIR and FIR, and frankly I haven't found a decent English-language explanation of what they DO.
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IIR filtering is related to one of my favorite jokes (explaining the difference between math/science and engineering):
There's a game show and the contestants are a mathematician and an engineer (both male).
The host explains the game as follows: There's a beautiful model on the other side of the room. For each question the contestants answer correctly, they get to move half way toward the beautiful model.
At that point the mathematician throws his hands up in the air in anger: "What's the point! If I move halfway there every time, I can never get to the model! This is pointless." Then he storms off the stage.
The host then turns to the engineer and says, "after hearing that, why are you sticking around? You can never get to the model!"
The engineer says, "while everything he said was theoretically correct, I can get close enough for practical purposes."
(rim shot and laugh track here)
How does this relate to IIR filtering? The part of "you move x-fraction of the way toward the goal" is what IIR filtering is about. It's called "infinite impulse response" because you can NEVER get to the goal because you always approach it at a fixed fraction of the way there.
FIR filtering (Finite Impulse Response) means you actually get to achieve your goal (hence the "finite"). If the game show were changed to: "the model is 100 feel away and you get to move 10 feet closer with each answer", that would be an FIR filter - in 10 answers you would get to the final result.
(my answer about how we're filtering is in a future post - I didn't want to clutter my joke with too much other stuff)