Showing posts with label FFT. Show all posts
Showing posts with label FFT. Show all posts

Wednesday, March 2, 2016

Thinking outside the box

I'm currently enrolled in the degree program Georgia Tech offers through Udacity. It's called OMSCS. I'm taking Knowledge Based Artificial Intelligence:Cognitive Systems.

The primary project we are working on is Ravens Progressive Matrices.

I have tons of ideas, and approaches. I'll talk about one that I'm experimenting with (and have no idea if it'll work).

One thought that crossed my mind was what if i could think of these problems as a time relationship. Could I apply a Fast Fourier Transform (FFT)? Well I am giving it a shot.

First I took a line by line reading of the image, then layed it end to end. So in a way you have a all kinds of crazy waveform.

Next I used numpy to convert to the Power Domain using numpy.fft.fft(array).

I'm not much further than this, but I did try dividing A by B and A by C and graphing these ratios along with inverse FFT'ing.

I thought the graphs looked really neat. So I am going to leave a few here for your enjoyment.

Which by the way I should note, I have no idea what I'm doing here, it's experimentation and who knows if these graphs are even logical, but they're cool looking.

A/C
A/B


Original Images
C
A
B
Have a good one, I'll probably post more about this in the future.