Howtosignalprocessing
- What is the minimum number of samples for fast Fourier transformation?
- What is the sampling frequency in FFT?
- How does sampling frequency affect FFT?
- What is 64 point FFT?
What is the minimum number of samples for fast Fourier transformation?
The fast Fourier transform (FFT) is a computer algorithm developed by James Cooley and John Tukey. The algorithm computes the coefficients for the Fourier series that represents a sequence. The number of samples (N) in the FFT must be an integer power of 2.
What is the sampling frequency in FFT?
The sampling rate or sampling frequency fs of the measuring system (e.g. 48 kHz). This is the average number of samples obtained in one second (samples per second). The selected number of samples; the blocklength BL. This is always an integer power to the base 2 in the FFT (e.g., 2^10 = 1024 samples)
How does sampling frequency affect FFT?
The amplitude of the DFT (FFT) is proportional to the number of samples. Therefore, if you sample for twice as long at the same sampling frequency, or if you sample for the same duraiton but twice as fast, you will have twice as many data points, and the DFT amplitude will be twice as large. See examples below.
What is 64 point FFT?
The 64-point FFT is realized by decomposing it into a two-dimensional structure of 8-point FFTs. This approach reduces the number of required complex multiplications compared to the conventional radix-2 64-point FFT algorithm. The complex multiplication operations are realized using shift-and-add operations.
