Howtosignalprocessing
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.
- How does sampling frequency affect FFT?
- What is the relationship between sampling rate and frequency?
- How can frequency resolution of FFT be improved?
- What is the number of samples sample values that we usually choose for FFT?
- What do you mean by frequency resolution in DFT?
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 the relationship between sampling rate and frequency?
Sampling rate determines the sound frequency range (corresponding to pitch) which can be represented in the digital waveform. The range of frequencies represented in a waveform is often called its bandwidth.
How can frequency resolution of FFT be improved?
To increase the frequency resolution for a given frequency range, increase the number of points acquired at the same sampling frequency. For example, acquiring 2,048 points at 1.024 kHz would have yielded ∆f = 0.5 Hz with frequency range 0 to 511.5 Hz.
What is the number of samples sample values that we usually choose for FFT?
The number of samples (N) in the FFT must be an integer power of 2. Therefore, N = 2p, where p is a positive integer. This rule minimizes the number of multiplications—and therefore the computation time—needed to compute the coefficients of the Fourier series.
What do you mean by frequency resolution in DFT?
For the DFT, the resolution is equal to fs/N, from Equation 4.8. So, for a given sampling frequency, the more samples (N) in the signal, the smaller the frequency increment between successive DFT data points. The more points sampled, the higher the spectral resolution.
