[severino]

I took a look at the source, as I was curious about how does one perform a FFT of a signal, but stumbled upon this. Could somebody explain to me what this calculation does? (in is the audio signal, if I'm not wrong)

  window := make([]float64, len(in))
  for i, x := range in {
      window[i] = float64(x) * (0.54 - 0.46*math.Cos(2*math.Pi*float64(i)/float64(len(in)-1)))
 

Thanks

[geolqued]

It looks like a windowing function. Used to turn continuous data into segments of data for FFT processing. https://en.m.wikipedia.org/wiki/Window_function

[max-m]

From that article, that's the original Hamming windows with a_0 = 0.54 and a_1 = 0.46.

> Setting a_0 to approximately 0.54, or more precisely 25/46, produces the Hamming window, proposed by Richard W. Hamming. That choice places a zero-crossing at frequency 5π/(N − 1), which cancels the first sidelobe of the Hann window, giving it a height of about one-fifth that of the Hann window. The Hamming window is often called the Hamming blip when used for pulse shaping.

[vsnf]

This is the kind of discovery that settles all debate in my mind that I could have ever been an electrical engineer, or any kind of mathematician.

[dylan604]

This is pretty much how I feel every time delving into FFTs. Like, I get the concept, but something in my brain just shuts off when it comes to actually trying to grok it. I do however very much appreciate those that have created software where I just provide --input and they handle the rest.

[flyinghamster]

I also have trouble wrapping my head around all of this, and complex numbers, for that matter. Never mind that I'm employing this stuff all the time in GNU Radio.