The many properties of the
DFT become really straightforward
(
very similar to the
Fourier Series) once we have once concept
down:
Circular Shifts.
Circular shifts
We can picture
periodic sequences as having discrete
points on a circle as the domain
Shifting by mm,
fn+m
f
n
m
, corresponds to rotating the cylinder
mm notches ACW (counter
clockwise). For
m=-2
m
-2
, we get a shift equal to that in the following
illustration:
To cyclic shift we follow these steps:
1) Write
fn
f
n
on a cylinder, ACW
2) To cyclic shift by mm, spin
cylinder m spots ACW
fn→f
((
n
+
m
))
N
→
f
n
f
((
n
+
m
))
N
Example 1
If
fn=01234567
f
n
0
1
2
3
4
5
6
7
, then
f
((
n
-
3
))
N
=34567012
f
((
n
-
3
))
N
3
4
5
6
7
0
1
2
It's called circular shifting, since we're moving
around the circle. The usual shifting is called "linear shifting"
(shifting along a line).
Notes on circular shifting
f
((
n
+
N
))
N
=fn
f
((
n
+
N
))
N
f
n
Spinning NN spots is the same
as spinning all the way around, or not spinning at all.
f
((
n
+
N
))
N
=f
((
n
-
(
N
-
m
)
))
N
f
((
n
+
N
))
N
f
((
n
-
(
N
-
m
)
))
N
Shifting ACW mm is equivalent to
shifting CW
N-m
N
m
f
((
-
n
))
N
f
((
-
n
))
N
The above expression, simply writes the values of
fn
f
n
clockwise.
Circular shifts and the DFT
theorem 1: Circular Shifts and DFT
If
fn
↔
DFT
Fk
f
n
↔
DFT
F
k
then
f
((
n
-
m
))
N
↔
DFT
ⅇ-ⅈ2πNkmFk
f
((
n
-
m
))
N
↔
DFT
2
N
k
m
F
k
(i.e. circular shift in time domain =
phase shift in DFT)
Proof
fn=1N∑k=0N-1Fkⅇⅈ2πNkn
f
n
1
N
k
0
N
1
F
k
2
N
k
n
(1)
so phase shifting the DFT
fn=1N∑k=0N-1Fkⅇ-ⅈ2πNknⅇⅈ2πNkn=1N∑k=0N-1Fkⅇⅈ2πNkn-m=f
((
n
-
m
))
N
f
n
1
N
k
0
N
1
F
k
2
N
k
n
2
N
k
n
1
N
k
0
N
1
F
k
2
N
k
n
m
f
((
n
-
m
))
N
(2)
"My introduction to signal processing course at Rice University."