Spring 2018


Mon Jan 29


I'm having some trouble getting the discrete transform to look as it should, but here's what I have so far (the notebook is attached).


I made a few small changes and converted to html (jupyter nbconvert filename) to make it easier to see without downloading.

I think this is close, though I haven't looked closely enough at your definitions - we should discuss.

Talk to you tomorrow.

We should do a tiny (like N=4) example with some dirt simple (like y=[1,1,0,0] or [1,-1,1,-1] or [1,1,1,1]) inputs to see if we make sense of those cases. That should make it clearer what the output k=0...(N-1) components mean.

Jim in class

I showed you two more notebook files: fourier.ipynb (looking at the N=4 case , plotting the basis functions, calculating the fourier coefficients as a dot products) and fourier_128_tophat (just the transform with N=128 for a "tophat" function __--__ .)

The .ipynb and .html files are attached.

attachments [paper clip]

  last modified size
TXT Week1.ipynb Tue May 28 2024 06:14 pm 37K
TXT Week1_jim.html Tue May 28 2024 06:14 pm 277K
TXT Week1_jim.ipynb Tue May 28 2024 06:14 pm 23K
TXT fourier.html Tue May 28 2024 06:14 pm 328K
TXT fourier.ipynb Tue May 28 2024 06:14 pm 69K
TXT fourier_128_tophat.html Tue May 28 2024 06:14 pm 294K
TXT fourier_128_tophat.ipynb Tue May 28 2024 06:14 pm 35K