(Computing the Fourier Transform)
(Computing the Fourier Transform)
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Compute the Fourier Transform of the signal
 
Compute the Fourier Transform of the signal
  
<math>\ x(t)= t \sin(2 \pi t+ \pi/4) </math>
+
<math>\ x(t)= \int_{-\infty}^{t} \tau \sin(2 \pi \tau+ \pi/4) d\tau </math>
  
 
By definition the Fourier Transform of a signal is defined as:
 
By definition the Fourier Transform of a signal is defined as:
  
<math>X(\omega)=\int_{-\infty}^{\infty}x(t)e^{-j\omega t}dt</math>
+
<math> F[x(t)] = X(\omega)=\int_{-\infty}^{\infty}x(t)e^{-j\omega t}dt</math>
  
 
First expressing the signal in as a Fourier series:
 
First expressing the signal in as a Fourier series:
  
However before finding the transform we note that multiplication in the time domain is just differentiation in the frequency domain. So the game plan is to find the Fourier series of x(t)/t then differentiate it with respect to w in the frequency space.
+
However before finding the transform we note that integration in the time domain is just division in the frequency domain. So the game plan is to find the Fourier series of x'(t) then divide by the frequency in the frequency space.
  
<math>\ x1(t)=\sin(2\pi t+ \pi/4) = \frac{e^{2 \pi jt + \pi/4}{2j}</math>
+
<math>\ x'(t)=\sin(2\pi t+ \pi/4) = \frac{e^{2 \pi jt + \pi/4}}{2j} - \frac{e^{-2 \pi jt -j \pi/4}}{2j}</math>
 +
 
 +
<math> X'(\omega)=\int_{-\infty}^{\infty} \frac{e^{j \pi/4}}{2j} e^{j2 \pi} e^{-j\omega t}dt - \int_{-\infty}^{\infty} \frac{e^{-j \pi/4}}{2j} e^{-j2 \pi} e^{-j\omega t}dt</math>
 +
 
 +
Using some foresight we see that a straight up integration of the expression above will yield something infinite or indeterminate, we take advantage of the known Fourier transform of a complex exponential.
 +
 
 +
<math> X'(\omega)= \frac{e^{j \pi/4}}{2j} F[e^{j2 \pi}] - \frac{e^{-j \pi/4}}{2j} F[e^{-j2 \pi}] </math>
 +
 
 +
Noting that <math>\ F[e^{j\omega_0}] = 2 \pi \delta(\omega - \omega_0) </math>
 +
 
 +
<math>\ X'(\omega) = j \pi \delta(\omega + 2\pi) e^{-j \pi /4}- j \pi \delta(\omega + 2\pi) e^{j \pi /4}</math>
 +
 
 +
Therefore:
 +
 
 +
<math> X(\omega) =\frac{j \pi}{\omega} \delta(\omega + 2\pi) e^{-j \pi /4}- \frac{j \pi}{w} \delta(\omega + 2\pi) e^{j \pi /4}

Revision as of 16:44, 8 October 2008

Computing the Fourier Transform

Compute the Fourier Transform of the signal

$ \ x(t)= \int_{-\infty}^{t} \tau \sin(2 \pi \tau+ \pi/4) d\tau $

By definition the Fourier Transform of a signal is defined as:

$ F[x(t)] = X(\omega)=\int_{-\infty}^{\infty}x(t)e^{-j\omega t}dt $

First expressing the signal in as a Fourier series:

However before finding the transform we note that integration in the time domain is just division in the frequency domain. So the game plan is to find the Fourier series of x'(t) then divide by the frequency in the frequency space.

$ \ x'(t)=\sin(2\pi t+ \pi/4) = \frac{e^{2 \pi jt + \pi/4}}{2j} - \frac{e^{-2 \pi jt -j \pi/4}}{2j} $

$ X'(\omega)=\int_{-\infty}^{\infty} \frac{e^{j \pi/4}}{2j} e^{j2 \pi} e^{-j\omega t}dt - \int_{-\infty}^{\infty} \frac{e^{-j \pi/4}}{2j} e^{-j2 \pi} e^{-j\omega t}dt $

Using some foresight we see that a straight up integration of the expression above will yield something infinite or indeterminate, we take advantage of the known Fourier transform of a complex exponential.

$ X'(\omega)= \frac{e^{j \pi/4}}{2j} F[e^{j2 \pi}] - \frac{e^{-j \pi/4}}{2j} F[e^{-j2 \pi}] $

Noting that $ \ F[e^{j\omega_0}] = 2 \pi \delta(\omega - \omega_0) $

$ \ X'(\omega) = j \pi \delta(\omega + 2\pi) e^{-j \pi /4}- j \pi \delta(\omega + 2\pi) e^{j \pi /4} $

Therefore:

$ X(\omega) =\frac{j \pi}{\omega} \delta(\omega + 2\pi) e^{-j \pi /4}- \frac{j \pi}{w} \delta(\omega + 2\pi) e^{j \pi /4} $

Alumni Liaison

Ph.D. on Applied Mathematics in Aug 2007. Involved on applications of image super-resolution to electron microscopy

Francisco Blanco-Silva