Discrete Fourier Transform frequency bin size

1. What is FFT bin size?
2. How do you find the number of frequency bins?
3. What is DFT size?
4. How many times faster is an FFT than a DFT for a block size of 256 samples?

What is FFT bin size?

The FFT size defines the number of bins used for dividing the window into equal strips, or bins. Hence, a bin is a spectrum sample , and defines the frequency resolution of the window. By default : N (Bins) = FFT Size/2.

How do you find the number of frequency bins?

frequency bins are intervals between samples in frequency domain. For example, if your sample rate is 100 Hz and your FFT size is 100, then you have 100 points between [0 100) Hz. Therefore, you divide the entire 100 Hz range into 100 intervals, like 0-1 Hz, 1-2 Hz, and so on.

What is DFT size?

If we look at the dimensions of the DFT result, we get 2+31*2 which is, again, 64 dimensions. Here is a visual representation of the matrix elements using the complex unit circle: The first row is the DC component or the bias. It only has real components.

How many times faster is an FFT than a DFT for a block size of 256 samples?

This means FFT is 32 times faster than DFT.