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PDF Matlab Exercises To Explain Discrete Fourier Transforms

To understand what a Discrete Fourier Transform (DFT) is how to compute a DFT ▫ efficiently using a fast Fourier Transform (FFT) and the advantages of using 

PDF Seminar 6 – DFT and Matlab code

Matlab's FFT function is an effective tool for computing the discrete Fourier transform of a signal The following code examples will help you to understand the

  • How do you write a Fourier transform in Matlab?

    Compute the Fourier transform of the signal, and create the vector f that corresponds to the signal's sampling in frequency space. y = fft(x); fs = 1/Ts; f = (0:length(y)-1)*fs/length(y);

  • Properties of the DFT
    The transform of a sum is the sum of the transforms: DFT(x+y) = DFT(x) + DFT(y).
    Likewise, a scalar product can be taken outside the transform: DFT(c*x) = c*DFT(x).
    These follow directly from the fact that the DFT can be represented as a matrix multiplication.

  • What is the formula for the discrete Fourier transform in Matlab?

    x ( n + 1 ) = 1 N ∑ k = 0 N - 1 X ( k + 1 ) W N - k n .
    W N = e - j 2 π / N .
    Note The MATLAB convention is to use a negative j for the fft function.
    This is an engineering convention; physics and pure mathematics typically use a positive j.

  • How do you calculate DFT in Matlab?

    Y = fft( X ) computes the discrete Fourier transform (DFT) of X using a fast Fourier transform (FFT) algorithm.
    Y is the same size as X .
    If X is a vector, then fft(X) returns the Fourier transform of the vector.

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