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4) Discrete Fourier Transform

Definition: let x[n] be a DT signal with Period N.

$ X [k] = \sum_{k=0}^{N-1} x[n].e^{-J.2pi.kn/N} $

$ x [n] = (1/N) \sum_{k=0}^{N-1} X[k].e^{J.2pi.kn/N} $

Derivation:

Digital signal are :

  • Finite Duration
  • Discrete

So the idea is, we need to discretize (ie sample) the Fourier Transform

$ X(w) = \sum_{n=-\infty}^{\infty} x[n].e^{-Jwn} >^{sampling}> X(k.2pi/N) = \sum x[n].e^{-J2pi.n.k/N} $

Note: if X(w) is band-limited and if N is big enough, we can reconstruct X(w)


Observe that : $ X(k.2pi/N) = \sum_{n=0}^{N-1} x_{p}[n].e^{-J.2pi.kn/N} $, where $ x_{p}[n] = \sum_{-\infty}^{\infty} x[n-lN] $ is periodic with N




$ S_{\tau}(t) = P_{T}(t) = \sum_{K=-\infty}^{\infty} \delta (t - KT) $ [Eq. 2]

Alumni Liaison

Sees the importance of signal filtering in medical imaging

Dhruv Lamba, BSEE2010