Line 3: Line 3:
 
Due in class, Friday October 15, 2010.  
 
Due in class, Friday October 15, 2010.  
  
The discussion page for this homework is [[Hw6ECE438 discussion|here]]. Feel free to share your answers/thoughts/questions on [[Hw5ECE438 discussion|that page]].  
+
The discussion page for this homework is [[Hw6ECE438_discussion|here]]. Feel free to share your answers/thoughts/questions on [[Hw6ECE438_discussion|that page]].  
  
 
----
 
----
Line 71: Line 71:
  
 
<br>  
 
<br>  
 
+
<br>
+
 
+
 
----
 
----
  
 
== Question 2  ==
 
== Question 2  ==
 +
Draw a complete flow diagram for a decimation-in-time FFT algorithm for an 8 point FFT. How many complex operations does your algorithm takes? How many operations would this  DFT computation take if you were using the summation formula (i.e., the definition of the DFT) instead?
  
 
----
 
----
  
 
== Question 3  ==
 
== Question 3  ==
 +
a) Draw a complete flow diagram for a decimation-in-time FFT algorithm for an 6 point FFT beginning with two three-point DFTs. How many complex operations does your algorithm takes? How many operations would this  DFT computation take if you were using the summation formula (i.e., the definition of the DFT) instead?
  
 +
b) Draw a complete flow diagram for a decimation-in-time FFT algorithm for an 6 point FFT beginning with three two-point DFTs. How many complex operations does your algorithm takes? Compare with your answers in part a).
 
----
 
----
 +
== Question 4 ==
  
 +
 +
----
 
[[2010 Fall ECE 438 Boutin|Back to ECE438, Fall 2010, Prof. Boutin]]
 
[[2010 Fall ECE 438 Boutin|Back to ECE438, Fall 2010, Prof. Boutin]]

Revision as of 09:27, 8 October 2010

Homework 6, ECE438, Fall 2010, Prof. Boutin

Due in class, Friday October 15, 2010.

The discussion page for this homework is here. Feel free to share your answers/thoughts/questions on that page.


Question 1

Consider the signal

$ x[n]=\cos \left( \omega_1 n \right)+ k \cos \left( \omega_2 n \right) $

where k is a real-valued constant.

a) Write a program that will

  1. Plot x[n].
  2. Compute the N point DFT X[k]. (Yes, you may use FFT routines.)
  3. Plot the magnitude of X[k].

Turn in a print out of your code.

b) Run your program and generate outputs for the cases shown below.

Case N $ \omega_1 $ k $ \omega_2 $
1 20 0.62831853
2 200 0.62831853 0 N/A
3 20 0.64402649 0 N/A
4 200 0.64402649 0 N/A
5 200 0.64402649 0.2 1.27234502
6 200 0.64402649 0.2 0.79168135



Question 2

Draw a complete flow diagram for a decimation-in-time FFT algorithm for an 8 point FFT. How many complex operations does your algorithm takes? How many operations would this DFT computation take if you were using the summation formula (i.e., the definition of the DFT) instead?


Question 3

a) Draw a complete flow diagram for a decimation-in-time FFT algorithm for an 6 point FFT beginning with two three-point DFTs. How many complex operations does your algorithm takes? How many operations would this DFT computation take if you were using the summation formula (i.e., the definition of the DFT) instead?

b) Draw a complete flow diagram for a decimation-in-time FFT algorithm for an 6 point FFT beginning with three two-point DFTs. How many complex operations does your algorithm takes? Compare with your answers in part a).


Question 4


Back to ECE438, Fall 2010, Prof. Boutin

Alumni Liaison

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

Francisco Blanco-Silva