Howtosignalprocessing
- Does FFT have to be power of 2?
- How can I make my FFT more accurate?
- Are FFTs limited to sizes that are powers of 2?
- What is the relation between DFT and FFT on the basic of computational power?
Does FFT have to be power of 2?
Sure, you can use a radix-2 FFT to compute FFTs for lengths not a power of 2 (but it is not as efficient as using methods specifically tailored to the factors of the sequence length).
How can I make my FFT more accurate?
The most intuitive way to increase the frequency resolution of an FFT is to increase the size while keeping the sampling frequency constant. Doing this will increase the number of frequency bins that are created, decreasing the frequency difference between each.
Are FFTs limited to sizes that are powers of 2?
1.6 Are FFTs limited to sizes that are powers of 2? No. The most common and familiar FFTs are “radix 2”. However, other radices are sometimes used, which are usually small numbers less than 10.
What is the relation between DFT and FFT on the basic of computational power?
Discrete Fourier Transform (DFT) is the discrete version of the Fourier Transform (FT) that transforms a signal (or discrete sequence) from the time domain representation to its representation in the frequency domain. Whereas, Fast Fourier Transform (FFT) is any efficient algorithm for calculating the DFT.
