Daily Blog 5

I started researching the constant Q transform (CQT) on Monday and found the transform differs from the discrete Fourier transform (DFT) in several ways but the most important difference is the constant Q transform analyzes an audio file on a logarithmic scale. At the lower frequencies, there are more "bins" for analysis than at the higher frequencies. The file is analyzed this way because humans can not distinguish a 2.5 Hz difference at higher frequencies but we can at the lower ones so the resolution of the window at the high frequencies (10 KHz to 20KHz) does not have to be as high as at the lower frequencies.

Like the DFT, the CQT can be calculated by brute force or a short cut can be used. The fast Fourier transform (FFT) is the short cut for the DFT. The FFT is used in the short cut for the CQT. The CQT is equal to multiplying the FFT by the spectral kernel of the data. I found a website with some sample code in MatLab: http://www.hans.fugal.net/research/cq-octave.

Yesterday, I spent most of the day rewriting some of my previous code in hopes of condensing and modifying it so I could use a generic class for both my DFT class and CQT class. Unfortunately, I only managed to crash what I had written so I am going to change it back and look to modify it after I have a working CQT.