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Next: Fast Fourier Transform (FFT) Up: fourier Previous: Matrix form of the

An Example

Consider a discrete signal $x[n]$ of $N=8$ complex components:

\begin{displaymath}{\bf x}=\left[
\begin{array}{c} x[0]  x[1]  x[2]  x[3] ...
...3,0)  (4,0)  (0,0)  (0,0)  (0,0)
\end{tabular} \right] \end{displaymath}

Note that Fourier transform is a complex transform. In general, the product of two complex numbers $A=A_r+j A_i$ and $B=B_r+j B_i$ is also complex:

\begin{displaymath}A \times B=(A_r+j A_i)(B_r+j B_i)=(A_rB_r-A_iB_i)+j(A_rB_i+A_iB_r) \end{displaymath}

The foreword discrete Fourier transform is:

\begin{displaymath}X[n]= X_r[n]+jX_i[n]=\sum_{m=0}^{N-1} x[m] e^{-j2\pi m n/N}
...
...=0}^{N-1} (x_r[m]+jx_i[m]) (cos(2\pi m n/N)-j\;sin(2\pi mn/N)) \end{displaymath}

or

\begin{displaymath}\left\{ \begin{array}{l}
X_r[n]=\sum_{m=0}^{N-1} x_r[m]cos(2...
..._i[m]cos(2\pi mn/N)-x_r[m]sin(2\pi m n/N)
\end{array} \right. \end{displaymath}

The inverse transform is:

\begin{displaymath}x[m]=x_r[m]+jx_i[m]=\frac{1}{N}\sum_{n=0}^{N-1} X[n] e^{j2\pi m n/N} \end{displaymath}

or

\begin{displaymath}\left\{ \begin{array}{l}
x_r[m]=\sum_{n=0}^{N-1} X_r[n]cos(2...
..._i[n]cos(2\pi mn/N)+X_r[n]sin(2\pi m n/N)
\end{array} \right. \end{displaymath}

These transforms can be expressed in matrix forms. For example, the forward transform is:

\begin{displaymath}\left[
\begin{array}{c} X[0]  X[1]  X[2]  X[3]  X[4] ...
...]  x[3]  x[4]  x[5]  x[6]  x[7]
\end{array} \right] \end{displaymath}

For this specific example of 8-point DFT, we have

\begin{displaymath}w[m,n]=e^{-j2\pi mn/N}=cos(2\pi mn/N)-j\;sin(2\pi mn/N)
=cos(\pi mn/4)-j\;sin(\pi mn/4) \end{displaymath}

and

\begin{displaymath}\left[ \begin{tabular}{r}
(9.0,0.0)  (-6.1,-4.1)  (2.0,...
...,0)  (4,0)  (0,0)  (0,0)  (0,0)
\end{tabular} \right]
\end{displaymath}

DFTcos.gif DFTsin.gif

If the signal $x[m]$ is real, then its spectrum $X[n]$ has the following properties:

dft1d_demo.gif


next up previous
Next: Fast Fourier Transform (FFT) Up: fourier Previous: Matrix form of the
Ruye Wang 2015-11-12