(New page: DTFT)
 
Line 1: Line 1:
DTFT
+
== Discrete Time Fourier Transform (DTFT) with example  ==
 +
 
 +
a Slecture by ECE Student Fabian Faes
 +
 
 +
Partly based on the ECE438 Fall 2014 lecture material of Prof. Mireille Boutin.
 +
 
 +
----
 +
 
 +
----
 +
 
 +
== Definition  ==
 +
 
 +
The discrete time fourier transform (DTFT) of a finite energy aperiodic signal x[n] can be given by the equation listed below. IT is a representation in terms of a complex exponential sequence <span class="texhtml">''e''<sup>''j''ω''n''</sup></span>, where <span class="texhtml">ω</span> is a real frequency variable.
 +
 
 +
<math>X(e^{j{\omega}}) = X({\omega}) = {\sum_{n = -{\infty}}^{\infty} x[n]e^{-j{\omega}n}}</math>
 +
 
 +
<span class="texhtml">''X''(ω)</span> can also be represented in terms of its magnitude and phase as shown below:
 +
 
 +
'''magnitude'''
 +
 
 +
<span class="texhtml">''X''(ω) =  | ''X''(ω) | ''e''<sup>''j''θω</sup></span>
 +
 
 +
'''phase'''
 +
 
 +
<math>{\theta}({\omega}) = {\angle}X({\omega})</math>
 +
 
 +
 
 +
----
 +
 
 +
 
 +
== Periodicity Property ==
 +
 
 +
We note that <math>X({\omega})</math> is periodic with period <math>2{\pi}</math> since
 +
 
 +
<math>X({\omega} + 2{\pi}) =  {\sum_{n = -{\infty}}^{\infty} x[n]e^{-j({\omega} + 2{\pi})n}}</math>
 +
 
 +
<math>X({\omega} + 2{\pi}) =  {\sum_{n = -{\infty}}^{\infty} x[n]e^{-j{\omega}n}e^{-j2{\pi}n}}</math>
 +
 
 +
<math>X({\omega} + 2{\pi}) =  {\sum_{n = -{\infty}}^{\infty} x[n]e^{-j{\omega}n}}</math>
 +
 
 +
<math>X({\omega} + 2{\pi}) =  X({\omega})</math>
 +
 
 +
for clarification <math>e^{-j2{\pi}n} = 1</math> since
 +
 
 +
<math>e^{-j2{\pi}n} = cos(2{\pi}) + jsin(2{\pi}n)</math>
 +
 
 +
<math>e^{-j2{\pi}n} = 1 + j0</math>
 +
 
 +
<math>e^{-j2{\pi}n} = 1</math>
 +
 
 +
However it is interesting to note that this does not apply if we are dealing with a continous signal. This is a common mistake made by students.
 +
 
 +
<math>e^{-j2{\pi}n} = (e^{-j2{\pi}})^n = 1^n = 1</math>
 +
 
 +
<math>e^{-j2{\pi}t} = (e^{-j2{\pi}})^t = 1^t {\neq} 1</math>
 +
 
 +
This is because t can lead to a <math>{\pm}</math> solution due to t not being a definite value such as n.
 +
 
 +
 
 +
----
 +
 
 +
== Complex Exponential Example ==

Revision as of 22:59, 30 September 2014

Discrete Time Fourier Transform (DTFT) with example

a Slecture by ECE Student Fabian Faes

Partly based on the ECE438 Fall 2014 lecture material of Prof. Mireille Boutin.



Definition

The discrete time fourier transform (DTFT) of a finite energy aperiodic signal x[n] can be given by the equation listed below. IT is a representation in terms of a complex exponential sequence ejωn, where ω is a real frequency variable.

$ X(e^{j{\omega}}) = X({\omega}) = {\sum_{n = -{\infty}}^{\infty} x[n]e^{-j{\omega}n}} $

X(ω) can also be represented in terms of its magnitude and phase as shown below:

magnitude

X(ω) = | X(ω) | ejθω

phase

$ {\theta}({\omega}) = {\angle}X({\omega}) $




Periodicity Property

We note that $ X({\omega}) $ is periodic with period $ 2{\pi} $ since

$ X({\omega} + 2{\pi}) = {\sum_{n = -{\infty}}^{\infty} x[n]e^{-j({\omega} + 2{\pi})n}} $

$ X({\omega} + 2{\pi}) = {\sum_{n = -{\infty}}^{\infty} x[n]e^{-j{\omega}n}e^{-j2{\pi}n}} $

$ X({\omega} + 2{\pi}) = {\sum_{n = -{\infty}}^{\infty} x[n]e^{-j{\omega}n}} $

$ X({\omega} + 2{\pi}) = X({\omega}) $

for clarification $ e^{-j2{\pi}n} = 1 $ since

$ e^{-j2{\pi}n} = cos(2{\pi}) + jsin(2{\pi}n) $

$ e^{-j2{\pi}n} = 1 + j0 $

$ e^{-j2{\pi}n} = 1 $

However it is interesting to note that this does not apply if we are dealing with a continous signal. This is a common mistake made by students.

$ e^{-j2{\pi}n} = (e^{-j2{\pi}})^n = 1^n = 1 $

$ e^{-j2{\pi}t} = (e^{-j2{\pi}})^t = 1^t {\neq} 1 $

This is because t can lead to a $ {\pm} $ solution due to t not being a definite value such as n.



Complex Exponential Example

Alumni Liaison

Basic linear algebra uncovers and clarifies very important geometry and algebra.

Dr. Paul Garrett