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-
Discrete-Time Fourier
Transform
Chang-Su Kim
continuous time discrete time
periodic (series) CTFS DTFS
aperiodic (transform) CTFT DTFT
-
DTFT Formula and Its Derivation
-
DTFT Formula
DTFT
cf) CTFT
Note that in DT case, 𝑋(𝑒𝑗𝜔) is periodic with period 2𝜋 and the inverse transform is defined as a integral over one period
2
1[ ] ( )
2
( ) [ ]
j j n
j j n
n
x n X e e d
X e x n e
1( ) ( )
2
( ) ( )
j t
j t
x t X j e d
X j x t e dt
-
Examples
11
(a) [ 1]2
(b) [ 1] [ 1]
n
u n
n n
2 , 0(a) ( )
2 , 0
jwj w
X ej w
Find the Fourier transforms of
Find the inverse Fourier transform of
-
Derivation of DTFT from DTFS
x[n]
N-N-N1 N2
][~ nx
0
2
2
( )
( )
[ ]
1[ ]
N
N
jk n
k
k N
jk n
k
n N
x n a e
a x n eN
As , [ ] [ ]
and the DTFS formula becomes the desired DTFT formula
N x n x n
-
DTFT of Periodic Functions
0
0[ ] ( ) 2 ( )jk n F j
k k
k N k
x n a e Χ e a k
Periodic functions can also be represented as
Fourier Transforms
-
Examples
DTFT of periodic functions
0
(a) cosine function
[ ] cos
(b) periodic impulse train
[ ] [ ] k
x n w n
y n n kN
-
Selected Properties of DTFT
-
Shift in Frequency
This property can be used to
convert a lowpass filter to a
highpass one, or vice versa
0 0( )
( )
[ ] ( )
( 1) [ ] ( )
jw n j w wF
Fn j w
e x n X e
x n X e
-
Differentiation in Frequency
( )[ ]
jwF dX enx n j
dw
-
Parseval’s Relation
22
2
1[ ] ( )
2
jw
n
x n X e dw
-
Time Expansion
otherwise , 0
of multipleinteger an is if , ]/[][)(
knknxnx k
. . .
][nx
1 2 3
][)3( nx
3 6 94 5
For a natural number k, we define
)(][ )(jkF
k enx
-
Convolution
[ ] [ ] [ ] ( ) ( ) ( )F jw jw jwy n x n h n Y e X e H e
-
Multiplication
( )
1 2 1 22
1[ ] [ ] [ ] ( ) ( ) ( )
2
F j j jy n x n x n Y e X e X e d
Multiplication in time domain corresponds to the
periodic convolution in frequency domain
-
Summary of Fourier Series and
Transform Expressions
-
All the Four Formulas
CT DT
Periodic(series)
CTFS DTFS
Aperiodic(transform)
CTFT DTFT
0
0
( ) ,
1( )
jk t
k
k
jk t
k
T
x t a e
a x t e dtT
2
2
( )
( )
[ ]
1[ ]
N
N
jk n
k
k N
jk n
k
n N
x n a e
a x n eN
2
1[ ] ( )
2
( ) [ ]
j j n
j j n
n
x n X e e d
X e x n e
1( ) ( )
2
( ) ( )
j t
j t
x t X j e d
X j x t e dt
-
Time Frequency
aperiodic continuousperiodic discretediscrete periodiccontinuous aperiodic
[ ], ( )x n x t
[ ], ( )x n x t
[ ]x n
( )x t
( ), ( )jX e X j
( ), ( )jX e X j
( )jX e
( )X j
Properties
CT DT
Periodic(series)
CTFS DTFS
Aperiodic(transform)
CTFT DTFT
0
0
0
( )
1(
) )
)
( 2 (
jk t
k
k
jk t
k
k
k
T
x t a e
a x t e d
a k
t
X
T
j
2
2
( )
(
0
)
[ ]
1[
( 2 (
]
) )
N
N
jk n
k
k N
jk n
k
k
N
k
n
j
x n a e
a x n eN
Χ e a k
2
1[ ] ( )
2
( ) [ ]
j j n
j j n
n
x n X e e d
X e x n e
1( ) ( )
2
( ) ( )
j t
j t
x t X j e d
X j x t e dt
sampling of continuous
functions => discrete
-
Dualities
CT DT
Periodic(series)
CTFS DTFS
Aperiodic(transform)
CTFT DTFT
0
0
( ) ,
1( )
jk t
k
k
jk t
k
T
x t a e
a x t e dtT
2
2
( )
( )
[ ]
1[ ]
N
N
jk n
k
k N
jk n
k
n N
x n a e
a x n eN
2
1[ ] ( )
2
( ) [ ]
j j n
j j n
n
x n X e e d
X e x n e
1( ) ( )
2
( ) ( )
j t
j t
x t X j e d
X j x t e dt
-
Dualities
CT DT
Periodic(series)
CTFS DTFS
Aperiodic(transform)
CTFT DTFT
0
0
( ) ,
1( )
jk t
k
k
jk t
k
T
x t a e
a x t e dtT
2
2
( )
( )
[ ]
1[ ]
N
N
jk n
k
k N
jk n
k
n N
x n a e
a x n eN
2
1[ ] ( )
2
( ) [ ]
j j n
j j n
n
x n X e e d
X e x n e
1( ) ( )
2
( ) ( )
j t
j t
x t X j e d
X j x t e dt
-
Dualities
CT DT
Periodic(series)
CTFS DTFS
Aperiodic(transform)
CTFT DTFT
0
0
( ) ,
1( )
jk t
k
k
jk t
k
T
x t a e
a x t e dtT
2
2
( )
( )
[ ]
1[ ]
N
N
jk n
k
k N
jk n
k
n N
x n a e
a x n eN
2
1[ ] ( )
2
( ) [ ]
j j n
j j n
n
x n X e e d
X e x n e
1( ) ( )
2
( ) ( )
j t
j t
x t X j e d
X j x t e dt
-
Causal LTI Systems Described
by Difference Equations
-
Linear Constant-Coefficient Difference
Equations
The DE describes the relation between the input x[n]
and the output y[n] implicitly
In this course, we are interested in DEs that
describe causal LTI systems
Therefore, we assume the initial rest condition
0 0
[ ] [ ]N M
k k
k k
a y n k b x n k
0 0If [ ] 0 for , then [ ] 0 forx n n n y n n n
-
Frequency Response
What is the frequency response H(ejw) of the
following system?
It is given by
0
0
( )
M jkw
kjw k
N jkw
kk
b eH e
a e
0 0
[ ] [ ]N M
k k
k k
a y n k b x n k
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Example
3 1[ ] [ 1] [ 2] 2 [ ],
4 8
1[ ] [ ]. What is [ ]?
4
n
y n y n y n x n
x n u n y n
Q)
-
Analogy between Differential Equations
and Difference Equations
Many properties, learned in differential equations,
can be applied to solve interesting problems
described by difference equations
Fibonacci sequence
a0 = a1 = 1
an = an-1 + an-2 (n≥2)
Golden ratio = 1.61803
-
Golden Ratio
Golden rectangle is said to be the most visually pleasing geometric
form
1
1.618
-
Golden Ratio
Golden rectangle is said to be the most visually
pleasing geometric form
1
1.618