Dft filtering

1. What is Fourier filtering?
2. How linear filtering is done using FFT?
3. What is DFT used for?
4. What is filtering in DFT?

What is Fourier filtering?

The Fourier filter is a type of filtering function that is based on manipulation of specific frequency components of a signal. It works by taking the Fourier transform of the signal, then attenuating or amplifying specific frequencies, and finally inverse transforming the result.

How linear filtering is done using FFT?

Step 1: Take the L samples of data sequence ��(��). Append M – 1 extra zeros to this block of data so that its length is L + M – 1. Step 2: Append L – 1 extra zeros to the FIR filter so that its length is L + M – 1. Step 3: Convolve the two sequences circularly using FFT as shown in Fig.

What is DFT used for?

The Discrete Fourier Transform (DFT) is of paramount importance in all areas of digital signal processing. It is used to derive a frequency-domain (spectral) representation of the signal.

What is filtering in DFT?

DFT provides an alternative approach to time domain convolution. It can be used to perform linear filtering in frequency domain. Thus,Y(ω)=X(ω). H(ω)⟷y(n). The problem in this frequency domain approach is that Y(ω), X(ω) and H(ω) are continuous function of ω, which is not fruitful for digital computation on computers.