How can I decide proper FFT length(size)?

1. How do I choose my FFT size?
2. What is transform length in FFT?
3. What is a perfect FFT?
4. How the length of window is decided in DSP?

How do I choose my FFT size?

The frequency resolution is equal to the sampling frequency divided by FFT size. For example, an FFT of size 256 of a signal sampled at 8000Hz will have a frequency resolution of 31.25Hz. If the signal is a sine wave of 110 Hz, the ideal FFT would show a sharp peak at 110Hz.

What is transform length in FFT?

The execution time of fft depends on the length of the transform. Transform lengths that have only small prime factors result in significantly faster execution time than those that have large prime factors. In this example, the signal length L is 44,101, which is a very large prime number.

What is a perfect FFT?

all frequency values except 10 Hz, where its value is −256i. The magnitude at this point is 256, and when we divide by N/2 = 512/2 = 256, we get a modified amplitude of exactly 1 V – the FFT is perfect.

How the length of window is decided in DSP?

Windowing works by forcing your data smoothly to zero at exactly the start and end of the sequence, but not before. Shortening your window destroys information unnecessarily. So your window length should match the length of your sample sequences. For instance, with 1024 samples, your window length should be 1024.