- 1.
- Implicit in the notion of causality is a temporal relationship between a
system input and a system response. To say that a given input produces a
certain system response implies that the input chronologically precedes its
effect. A common way of expressing this is that a response must not anticipate
its cause or input. Stated in mathematical notation: h(t)=0, for t<0.
- 2.
- For an even function, x(-t) = x(t). By the definition of the Fourier
transform,
The righthand equality follows from Euler's Theorem:

Substituting -t for t in the expression fo X(f) gives
Comparing the expressions for
and
, we notice that
they differ only by the sign of the imaginary part of the integrand. Since for a
given complex number r = a + bi,
, we can conclude that
.
- 3.
- For an odd function, y(-t) = -y(t).
By the definition of the Fourier transform,
The righthand equality follows from Euler's Theorem:

Substituting -t for t in the expression for Y(f) gives
Comparing the expressions for
and
, we notice that
the latter is the negative of the complex conjugate of the former; that is,

- 4.
-
h(t) = he(t) + ho(t)
where
![\begin{displaymath}
h_{e}(t) = \frac{1}{2}[h(t) + h(-t)]
\end{displaymath}](img10.gif)
and
![\begin{displaymath}
h_{o}(t) = \frac{1}{2}[h(t) - h(-t)]
\end{displaymath}](img11.gif)
To show that he(t) is even, we must demonstrate that he(t) =
he(-t). Substituting -t for t in the above expression gives
![\begin{displaymath}
h_{e}(-t)= \frac{1}{2}[h(-t) + h(t)]
\end{displaymath}](img12.gif)
Applying the commutative property of addition gives
![\begin{displaymath}
h_{e}(-t)=\frac{1}{2}[h(t) + h(-t)] = h_{e}(t)
\end{displaymath}](img13.gif)
Hence, he(t) is an even function.
Similarly, to show that ho(t) is odd, we must demonstrate that ho(-t) =
-ho(t). Substituting -t for t in the expression for ho(t) gives
Hence, ho(t) is an odd function.
Finally, to establish that h(t)=he(t) + ho(t), we simply add the
expressions for he(t) and ho(t) and perform some algebra.
- 5.
- Separating the real valued function h(t) into its odd and even components, we
make use of the linearity of the Fourier transform to write:

Invoking the result from part a) that the Fourier transform of an even function
is the complex conjugate of the Fourier transform of that function, we can
express the Fourier transform of the even part of h(t) as follows:

Recalling the result from part b) that the Fourier transform of an odd function
is the negative complex conjugate of the Fourier transform of that function, we
can express the Fourier transform of the odd part of h(t) as follows:

- 6.
- h(t) is a pulse of centered around
of width one and height
one. To validate the results from parts e) and d), we must rewrite h(t) as the
sum of even and odd parts, find the respective Fourier transforms, and take the
superposition of the two transforms.
The Fourier transform of a pulse of height and width one centered around
is given by

The even part of h(t) is given by
![\begin{displaymath}
h_{e}(t) = \frac{1}{2}[h(t) + h(-t)]
\end{displaymath}](img20.gif)
which graphically represents a pulse centered around
of width one
and height
, along with its reflection across the y-axis.
Applying superposition, we can find the Fourier transform of the sum of these
two pulses by adding the Fourier transforms of the individual pulses. For the
pulse component centered around
,

For the pulse component centered around
,

By superposition,
The odd part of h(t) is given by
![\begin{displaymath}
h_{o}(t) = \frac{1}{2}[h(t) - h(-t)]
\end{displaymath}](img27.gif)
which graphically represents a pulse centered around
of width one
and height
, in addition to its reflection across the origin,
centered around
of height
and width one. Using the
same procedure as with the even part of h(t), we can find
by
taking the superposition of the separate pulses comprising ho(t).
For the pulse component centered around
we have

For the pulse component centered around
we have

Again by superposition,
Thus
Simplification yields

which agrees with our original result for
.