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Decimation in Time

The DFT is defined by

$\displaystyle X(k) = \sum_{n=0}^{N-1} x(n) W_N^{kn}, \quad k=0,1,2,\ldots,N-1,

where $ x(n)$ is the input signal amplitude at time $ n$ , and

$\displaystyle W_N \isdef e^{-j\frac{2\pi}{N}}.\quad \hbox{(primitive $N$th root of unity)}

Note that $ W_N^N=1$ .

When $ N$ is even, the DFT summation can be split into sums over the odd and even indexes of the input signal:

$\displaystyle X(\omega_k)$ $\displaystyle \isdef$ $\displaystyle \DFTn{N,k}{x} \isdef \sum_{n=0}^{N-1} x(n) \emjoknT,
\quad \omega_k \isdef \frac{2\pi k}{NT}$  
  $\displaystyle =$ $\displaystyle \sum_{{\stackrel{n=0}{\vspace{2pt}\mbox{\tiny$n$\ even}}}}^{N-2} x(n) \emjoknT + \sum_{{\stackrel{n=0}{\vspace{2pt}\mbox{\tiny$n$\ odd}}}}^{N-1} x(n) \emjoknT$  
  $\displaystyle =$ $\displaystyle \sum_{n=0}^{\frac{N}{2}-1} x(2n) \emjoktnp
+ e^{-j2\pi\frac{k}{N}}\sum_{n=0}^{\frac{N}{2}-1} x(2n+1) \emjoktnp,$  
  $\displaystyle =$ $\displaystyle \sum_{n=0}^{\frac{N}{2}-1} x_e(n) W_{N/2}^{kn} + W_N^k
\sum_{n=0}^{\frac{N}{2}-1} x_o(n) W_{N/2}^{kn}$  
  $\displaystyle \isdef$ $\displaystyle \DFTn{\frac{N}{2},k}{\hbox{\sc Downsample}_2(x)}$  
    $\displaystyle \mathop{\quad} +\;W_N^k\cdot\DFTn{\frac{N}{2},k}{\hbox{\sc Downsample}_2[\hbox{\sc Shift}_1(x)]},
\protect$ (A.1)

where $ x_e(n)\isdef x(2n)$ and $ x_o(n)\isdef x(2n+1)$ denote the even- and odd-indexed samples from $ x$ . Thus, the length $ N$ DFT is computable using two length $ N/2$ DFTs. The complex factors $ W_N^k=e^{-j\omega_k}=\exp(-j2\pi k/N)$ are called twiddle factors. The splitting into sums over even and odd time indexes is called decimation in time. (For decimation in frequency, the inverse DFT of the spectrum $ X(\omega_k)$ is split into sums over even and odd bin numbers $ k$ .)

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``Mathematics of the Discrete Fourier Transform (DFT), with Audio Applications --- Second Edition'', by Julius O. Smith III, W3K Publishing, 2007, ISBN 978-0-9745607-4-8.
Copyright © 2016-05-31 by Julius O. Smith III
Center for Computer Research in Music and Acoustics (CCRMA),   Stanford University