(New page: =Discrete-time Fourier transform of a window function= Used in ECE438. ---- Consider the perfect discrete-time window function <math>w[n]= \left\{ \begin{array}{ll} 1,&\text{ if }0 \...)
 
Line 1: Line 1:
 
=Discrete-time Fourier transform of a window function=
 
=Discrete-time Fourier transform of a window function=
 
Used in [[ECE438]].
 
Used in [[ECE438]].
 +
 +
This page can be used to study the frequency-domain behavior of a discrete-time window function, as its length increases.
 +
 
----
 
----
 
Consider the perfect discrete-time window function
 
Consider the perfect discrete-time window function
Line 9: Line 12:
 
0, & \text{ else}.
 
0, & \text{ else}.
 
\end{array}
 
\end{array}
  \right.</math>
+
  \right.,</math>
  
The DTFT of that window function is
+
for any integer values of n. Note that N represents the length of the window. The DTFT of this window function is
  
 
<math>W(\omega) =\frac{e^{\frac{-j \omega (N-1)}{2}} \sin\left( \frac{\omega N}{2}\right)}{\sin \left( \frac{\omega}{2} \right)}</math>.
 
<math>W(\omega) =\frac{e^{\frac{-j \omega (N-1)}{2}} \sin\left( \frac{\omega N}{2}\right)}{\sin \left( \frac{\omega}{2} \right)}</math>.
Line 27: Line 30:
 
[[Image:W_of_omega_N_equal_10000.png|500px]]
 
[[Image:W_of_omega_N_equal_10000.png|500px]]
  
Observe the close resemblance of this graph to that of the magnitude of the Fourier transform of the corresponding continuous-time window.  
+
Observe the close resemblance of this graph to that of the magnitude of the Fourier transform of the signal <math>x[n]=1</math>, for any n integer (in other words, an "infinite-length" window).
 
----
 
----
 
[[ECE438|Back to ECE438]]
 
[[ECE438|Back to ECE438]]
  
 
[[2010_Fall_ECE_438_Boutin|Back to ECE438 Fall 2010]]
 
[[2010_Fall_ECE_438_Boutin|Back to ECE438 Fall 2010]]

Revision as of 08:43, 27 September 2010

Discrete-time Fourier transform of a window function

Used in ECE438.

This page can be used to study the frequency-domain behavior of a discrete-time window function, as its length increases.


Consider the perfect discrete-time window function

$ w[n]= \left\{ \begin{array}{ll} 1,&\text{ if }0 \leq n < N \\ 0, & \text{ else}. \end{array} \right., $

for any integer values of n. Note that N represents the length of the window. The DTFT of this window function is

$ W(\omega) =\frac{e^{\frac{-j \omega (N-1)}{2}} \sin\left( \frac{\omega N}{2}\right)}{\sin \left( \frac{\omega}{2} \right)} $.


Below is the graph of the magniture of $ W(\omega) $ for $ N=15 $.

W of omega N equal 15.png


Below is the graph of the magniture of $ W(\omega) $ for $ N=100 $. Observe that the ripples are "thinner" and more numerous than in the previous case of $ N=10 $.

W of omega N equal 100.png


Below is the graph of the magniture of $ W(\omega) $ for $ N=10000 $.

W of omega N equal 10000.png

Observe the close resemblance of this graph to that of the magnitude of the Fourier transform of the signal $ x[n]=1 $, for any n integer (in other words, an "infinite-length" window).


Back to ECE438

Back to ECE438 Fall 2010

Alumni Liaison

Prof. Math. Ohio State and Associate Dean
Outstanding Alumnus Purdue Math 2008

Jeff McNeal