Next, we'll derive the FT of some basic continuous-time signals. Table 1 summarizes these transform pairs.
Let's begin with the rectangular pulse
rect
(
t
,
τ
)
≡
1
,
t
≤
τ
/
2
0
,
t
>
τ
/
2
rect
(
t
,
τ
)
≡
1
,
t
≤
τ
/
2
0
,
t
>
τ
/
2
(1)
The pulse function, rect(t,τ)rect(t,τ) is shown in Figure 1. Substituting x(t)=rect(t,τ)x(t)=rect(t,τ) into (Reference) gives
X
(
j
Ω
)
=
∫
-
τ
/
2
τ
/
2
e
-
j
Ω
t
d
t
=
-
1
j
Ω
e
-
j
Ω
t
-
τ
/
2
τ
/
2
=
1
j
Ω
e
j
Ω
τ
/
2
-
e
-
j
Ω
τ
/
2
=
τ
sin
(
Ω
τ
/
2
)
Ω
τ
/
2
=
τ
sinc
(
Ω
τ
/
2
π
)
X
(
j
Ω
)
=
∫
-
τ
/
2
τ
/
2
e
-
j
Ω
t
d
t
=
-
1
j
Ω
e
-
j
Ω
t
-
τ
/
2
τ
/
2
=
1
j
Ω
e
j
Ω
τ
/
2
-
e
-
j
Ω
τ
/
2
=
τ
sin
(
Ω
τ
/
2
)
Ω
τ
/
2
=
τ
sinc
(
Ω
τ
/
2
π
)
(2)
A plot of X(jΩ)X(jΩ) is shown in Figure 1.
Note that when τ=0τ=0, X(jΩ)=1X(jΩ)=1.
We now have the following transform pair:
rect
(
t
,
τ
)
↔
τ
sin
(
Ω
τ
/
2
)
Ω
τ
/
2
rect
(
t
,
τ
)
↔
τ
sin
(
Ω
τ
/
2
)
Ω
τ
/
2
(3)
The unit impulse function was described in (Reference). From the sifting property of the impulse function we find that
X
(
j
Ω
)
=
∫
-
∞
∞
δ
(
t
-
τ
)
e
-
j
Ω
t
d
t
=
e
-
jΩ
τ
X
(
j
Ω
)
=
∫
-
∞
∞
δ
(
t
-
τ
)
e
-
j
Ω
t
d
t
=
e
-
jΩ
τ
(4)
or
δ
(
t
-
τ
)
↔
e
-
jΩ
τ
δ
(
t
-
τ
)
↔
e
-
jΩ
τ
(5)
The complex exponential function, x(t)=ejΩ0tx(t)=ejΩ0t, has a Fourier Transform which is difficult to evaluate directly. It is easier to start with the Fourier Transform itself and work backwards using the inverse Fourier Transform. Suppose we want to find the time-domain signal which has Fourier Transform X(jΩ)=δ(Ω-Ω0)X(jΩ)=δ(Ω-Ω0). We can begin by using the inverse Fourier Transform (Reference)
x
(
t
)
=
1
2
π
∫
-
∞
∞
δ
(
Ω
-
Ω
0
)
e
j
Ω
t
d
Ω
=
1
2
π
e
Ω
t
x
(
t
)
=
1
2
π
∫
-
∞
∞
δ
(
Ω
-
Ω
0
)
e
j
Ω
t
d
Ω
=
1
2
π
e
Ω
t
(6)
This result follows from the sifting property of the impulse function. By linearity, we can then write
e
j
Ω
t
↔
2
π
δ
(
Ω
-
Ω
0
)
e
j
Ω
t
↔
2
π
δ
(
Ω
-
Ω
0
)
(7)
The cosine signal can be expressed in terms of complex exponentials using Euler's Identity
cos
(
Ω
0
t
)
=
1
2
e
j
Ω
0
t
+
e
-
j
Ω
0
t
cos
(
Ω
0
t
)
=
1
2
e
j
Ω
0
t
+
e
-
j
Ω
0
t
(8)
Applying linearity and the Fourier Transform of complex exponentials to the right side of Equation 8, we quickly get:
cos
(
Ω
0
t
)
↔
π
δ
(
Ω
-
Ω
0
)
+
π
δ
(
Ω
+
Ω
0
)
cos
(
Ω
0
t
)
↔
π
δ
(
Ω
-
Ω
0
)
+
π
δ
(
Ω
+
Ω
0
)
(9)
The real exponential function is given by x(t)=Ke-αtu(t)x(t)=Ke-αtu(t), where KK and αα are real constants. To find its FT, we start with the definition
X
(
j
Ω
)
=
K
∫
0
∞
e
-
α
t
e
-
j
Ω
t
d
t
=
K
∫
0
∞
e
-
(
α
+
j
Ω
)
t
d
t
=
-
K
α
+
j
Ω
e
-
(
α
+
j
Ω
)
t
0
∞
=
-
K
α
+
j
Ω
(
0
-
1
)
=
K
α
+
j
Ω
X
(
j
Ω
)
=
K
∫
0
∞
e
-
α
t
e
-
j
Ω
t
d
t
=
K
∫
0
∞
e
-
(
α
+
j
Ω
)
t
d
t
=
-
K
α
+
j
Ω
e
-
(
α
+
j
Ω
)
t
0
∞
=
-
K
α
+
j
Ω
(
0
-
1
)
=
K
α
+
j
Ω
(10)
therefore,
K
e
-
α
t
u
(
t
)
↔
K
α
+
j
Ω
K
e
-
α
t
u
(
t
)
↔
K
α
+
j
Ω
(11)
Table 1: Some common Fourier Transform pairs.
|
x
(
t
)
x
(
t
)
|
X
(
j
Ω
)
X
(
j
Ω
)
|
|
rect
(
t
,
τ
)
rect
(
t
,
τ
)
|
τ
sin
(
Ω
τ
/
2
)
Ω
τ
/
2
τ
sin
(
Ω
τ
/
2
)
Ω
τ
/
2
|
|
δ
(
t
-
τ
)
δ
(
t
-
τ
)
|
e
-
j
Ω
τ
e
-
j
Ω
τ
|
|
e
j
Ω
0
t
e
j
Ω
0
t
|
2
π
δ
(
Ω
-
Ω
0
)
2
π
δ
(
Ω
-
Ω
0
)
|
|
cos
(
Ω
0
t
)
cos
(
Ω
0
t
)
|
π
δ
(
Ω
-
Ω
0
)
+
π
δ
(
Ω
+
Ω
0
)
π
δ
(
Ω
-
Ω
0
)
+
π
δ
(
Ω
+
Ω
0
)
|
|
K
e
-
α
t
u
(
t
)
K
e
-
α
t
u
(
t
)
|
K
α
+
j
Ω
K
α
+
j
Ω
|
When working problems involving finding the Fourier Transform, it is often preferable to use a table of transform pairs rather than to recalculate the Fourier Transform from scratch. Often, transform pairs in can be combined with known Fourier Transform properties to find new Fourier Transforms.
Example 3.1 Find the Fourier Transform of:
y(t)=2e5tu(-t)y(t)=2e5tu(-t). Clearly, we can write y(t)=x(-t)y(t)=x(-t) where x(t)=2e-5tu(t)x(t)=2e-5tu(t). Therefore, we can combine the known transform of x(t)x(t) from Table 1, namely,
X
(
j
Ω
)
=
2
5
+
j
Ω
X
(
j
Ω
)
=
2
5
+
j
Ω
(12)
with the time reversal property found in (Reference):
x
(
-
t
)
↔
X
(
j
Ω
)
*
x
(
-
t
)
↔
X
(
j
Ω
)
*
(13)
to get the answer:
Y
(
j
Ω
)
=
2
5
-
j
Ω
Y
(
j
Ω
)
=
2
5
-
j
Ω
(14)