Continuous Time Fourier Series preserves signal energy
i.e.:
∫
0
T
|
f
(
t
)
|
2
d
t
=
T
∑
n
=
-
∞
∞
|
C
n
|
2
with
unnormalized
basis
e
j
2
π
T
n
t
∫
0
T
|
f
(
t
)
|
2
d
t
=
∑
n
=
-
∞
∞
|
C
n
'
|
2
with
unnormalized
basis
e
j
2
π
T
n
t
T
|
|
f
|
|
2
2
︸
L
2
[
0
,
T
)
e
n
e
r
g
y
=
|
|
C
n
'
|
|
2
2
︸
l
2
(
Z
)
e
n
e
r
g
y
∫
0
T
|
f
(
t
)
|
2
d
t
=
T
∑
n
=
-
∞
∞
|
C
n
|
2
with
unnormalized
basis
e
j
2
π
T
n
t
∫
0
T
|
f
(
t
)
|
2
d
t
=
∑
n
=
-
∞
∞
|
C
n
'
|
2
with
unnormalized
basis
e
j
2
π
T
n
t
T
|
|
f
|
|
2
2
︸
L
2
[
0
,
T
)
e
n
e
r
g
y
=
|
|
C
n
'
|
|
2
2
︸
l
2
(
Z
)
e
n
e
r
g
y
(1)
Given
f
(
t
)
→
C
T
F
S
c
n
g
(
t
)
→
C
T
F
S
d
n
Then
∫
0
T
f
(
t
)
g
*
(
t
)
d
t
=
T
∑
n
=
-
∞
∞
c
n
d
n
*
with
unnormalized
basis
e
j
2
π
T
n
t
∫
0
T
f
(
t
)
g
*
(
t
)
d
t
=
∑
n
=
-
∞
∞
c
n
'
(
d
n
'
)
*
with
normalized
basis
e
j
2
π
T
n
t
T
〈
f
,
g
〉
L
2
(
0
,
T
]
=
〈
c
,
d
〉
l
2
(
Z
)
Given
f
(
t
)
→
C
T
F
S
c
n
g
(
t
)
→
C
T
F
S
d
n
Then
∫
0
T
f
(
t
)
g
*
(
t
)
d
t
=
T
∑
n
=
-
∞
∞
c
n
d
n
*
with
unnormalized
basis
e
j
2
π
T
n
t
∫
0
T
f
(
t
)
g
*
(
t
)
d
t
=
∑
n
=
-
∞
∞
c
n
'
(
d
n
'
)
*
with
normalized
basis
e
j
2
π
T
n
t
T
〈
f
,
g
〉
L
2
(
0
,
T
]
=
〈
c
,
d
〉
l
2
(
Z
)
(2)
Energy
=
|
|
f
|
|
2
=
∫
-
∞
∞
|
f
(
t
)
|
2
d
t
=
∞
Power
=
lim
T
→
∞
Energy
in
[
0
,
T
)
T
=
lim
T
→
∞
T
∑
n
|
c
n
|
2
T
=
∑
n
∈
Z
|
c
n
|
2
(unnormalized
FS)
Energy
=
|
|
f
|
|
2
=
∫
-
∞
∞
|
f
(
t
)
|
2
d
t
=
∞
Power
=
lim
T
→
∞
Energy
in
[
0
,
T
)
T
=
lim
T
→
∞
T
∑
n
|
c
n
|
2
T
=
∑
n
∈
Z
|
c
n
|
2
(unnormalized
FS)
(3)
f
(
t
)
=
∑
n
=
-
∞
∞
c
n
e
j
2
π
T
n
t
→
FS
c
n
=
1
2
sin
π
2
n
π
2
n
energy
in
time
domain:
|
|
f
|
|
2
2
=
∫
0
T
|
f
(
t
)
|
2
d
t
=
T
2
apply
Parseval's
Theorem:
T
∑
n
|
c
n
|
2
=
T
4
∑
n
sin
π
2
n
π
2
n
2
=
T
4
4
π
2
∑
n
sin
π
2
n
2
n
2
=
T
π
2
π
2
4
+
∑
n
odd
1
n
2
︸
π
2
4
=
T
2
□
f
(
t
)
=
∑
n
=
-
∞
∞
c
n
e
j
2
π
T
n
t
→
FS
c
n
=
1
2
sin
π
2
n
π
2
n
energy
in
time
domain:
|
|
f
|
|
2
2
=
∫
0
T
|
f
(
t
)
|
2
d
t
=
T
2
apply
Parseval's
Theorem:
T
∑
n
|
c
n
|
2
=
T
4
∑
n
sin
π
2
n
π
2
n
2
=
T
4
4
π
2
∑
n
sin
π
2
n
2
n
2
=
T
π
2
π
2
4
+
∑
n
odd
1
n
2
︸
π
2
4
=
T
2
□
The inner product of two vectors/signals is the same as
the
ℓ2
ℓ
2
inner product of their expansion coefficients.
Let
b
i
b
i
be an orthonormal basis for a Hilbert Space
H
H.
x∈H
x
H
,
y∈H
y
H
x=∑
i
α
i
b
i
x
i
α
i
b
i
y=∑
i
β
i
b
i
y
i
β
i
b
i
then
〈x,y〉
H
=∑
i
α
i
β
i
¯
x
y
H
i
α
i
β
i
Applying the Fourier Series, we can go from
ft
f
t
to
c
n
c
n
and
gt
g
t
to
d
n
d
n
∫0Tftgt¯d
t
=∑
n
=−∞∞
c
n
d
n
¯
t
0
T
f
t
g
t
n
c
n
d
n
inner product in time-domain = inner product of Fourier
coefficients.
x=∑
i
α
i
b
i
x
i
α
i
b
i
y=∑
j
β
j
b
j
y
j
β
j
b
j
〈x,y〉
H
=〈∑
i
α
i
b
i
,∑
j
β
j
b
j
〉=∑
i
α
i
〈(
b
i
,∑
j
β
j
b
j
)〉=∑
i
α
i
∑
j
β
j
¯〈(
b
i
,
b
j
)〉=∑
i
α
i
β
i
¯
x
y
H
i
α
i
b
i
j
β
j
b
j
i
α
i
b
i
j
β
j
b
j
i
α
i
j
β
j
b
i
b
j
i
α
i
β
i
by using inner product rules
〈
b
i
,
b
j
〉=0
b
i
b
j
0
when
i≠j
i
j
and
〈
b
i
,
b
j
〉=1
b
i
b
j
1
when
i=j
i
j
If Hilbert space H has a ONB, then inner products are
equivalent to inner products in
ℓ2
ℓ
2
.
All H with ONB are somehow equivalent to
ℓ2
ℓ
2
.
square-summable sequences
are important
Energy of a signal = sum of squares of its expansion
coefficients
Let
x∈H
x
H
,
b
i
b
i
ONB
x=∑
i
α
i
b
i
x
i
α
i
b
i
Then
∥x∥H2=∑
i
|
α
i
|2
H
x
2
i
α
i
2
Directly from Plancharel
∥x∥H2=
〈x,x〉
H
=∑
i
α
i
α
i
¯=∑
i
|
α
i
|2
H
x
2
x
x
H
i
α
i
α
i
i
α
i
2
Fourier Series
1Tei
w
0
nt
1
T
w
0
n
t
ft=1T∑
n
c
n
1Tei
w
0
nt
f
t
1
T
n
c
n
1
T
w
0
n
t
∫0T|ft|2d
t
=∑
n
=−∞∞|
c
n
|2
t
0
T
f
t
2
n
c
n
2
"My introduction to signal processing course at Rice University."