Monday: Stupid FFTs

Mostly because they really only want nice evenly sampled data.  I could zero pad the data until it is evenly sampled, but then it's like a billion samples long, >97% of it being zero.  Since my sampling is basically of period A and period B, I kind of feel like I should be able to take the FFT(A_sampled) + FFT(B_sampled) and get something reasonable, but I can't find a proof of that already online, and it's too late to do it now.  But really, it should just be an extension of the linearity principle, right?  If F{g(t) + h(t)} = F{g(t)} + F{h(t)}, then we should be fine.  We just cheat a bit and let g(t) be those samples sampled at rate A, and h(t) be those samples sampled at rate B, then the total signal is just g(t) + h(t), so the fft can be separated into those two components.  Blammo.

Except proofs that end in "Blammo" probably aren't as rigorous as I'd really like.  I guess in the worst case scenario, I do have a LS periodogram program already written, so that could probably give me something like a reasonable answer.  That is kind of a O(N^2) operation, though, so it sucks next to the O(N log N) FFT method.

Ok, enough math rambling for today.

This might end up like the recurrent bears.

What are you doing, bears? Sears doesn't have anything in your size!

What are you doing, sheep? You're not zombies!

What are you doing lady? You're not...oh. Wait. Nevermind then.

• I totally had this problem in college with certain professors.  No matter how interesting the topic was, the voice was too soothing, so I'd always fall asleep. Even if I was in the front row. Like six feet away from where he was lecturing.
• Little known fact: lots of people in the 80s had an eye replaced with a screw.  Just for fun.
• I've kind of wanted to try this place, but it's in Waikiki, and parking sucks there.  Still, 25 layer katsu sounds interesting.
• Umbreon shoes.