The Fourier
transform of a real,
continuous-time signal
x(t)
MathType@MTEF@5@5@+=feaafeart1ev1aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVeYdOipfYlH8qipiY=Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciGacaGaaeaabaWaaeaaeaaakeaacaWG4bGaaiikaiaadshacaGGPaaaaa@398F@ is a complex-valued function defined by
where
w
is a real variable (frequency, in radians/second)
and j=−1
MathType@MTEF@5@5@+=feaafeart1ev1aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVeYhH8qipfea0xh9v8qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaamOAaiabg2da9maakaaabaGaeyOeI0IaaGymaaWcbeaaaaa@3925@.
A
plot of
|X(ω)|
MathType@MTEF@5@5@+=feaafeart1ev1aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVeYhH8qipfea0xh9v8qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaaiiFaiaadIfacaGGOaGaeqyYdCNaaiykaiaacYhaaaa@3B70@ vs w is called the magnitude spectrum of
x(t)
MathType@MTEF@5@5@+=feaafeart1ev1aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVeYdOipfYlH8qipiY=Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciGacaGaaeaabaWaaeaaeaaakeaacaWG4bGaaiikaiaadshacaGGPaaaaa@398F@,
and a plot of
∢X(ω)
MathType@MTEF@5@5@+=feaafeart1ev1aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVeYhH8qipfea0xh9v8qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaeSOiImLaaGPaVlaadIfacaGGOaGaeqyYdCNaaiykaaaa@3C23@ vs wis called the phase spectrum of
x(t)
MathType@MTEF@5@5@+=feaafeart1ev1aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVeYdOipfYlH8qipiY=Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciGacaGaaeaabaWaaeaaeaaakeaacaWG4bGaaiikaiaadshacaGGPaaaaa@398F@.
These plots, particularly the magnitude spectrum, provide a picture of the
frequency composition of the signal. For a real signal, the magnitude spectrum
is an even function of frequency,
|X(−ω)|=|X(ω)|
MathType@MTEF@5@5@+=feaafeart1ev1aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVeYdOipfYlH8qipiY=Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciGacaGaaeaabaWaaeaaeaaakeaacaGG8bGaamiwaiaacIcacqGHsislcqaHjpWDcaGGPaGaaiiFaiaaysW7cqGH9aqpcaaMe8UaaiiFaiaadIfacaGGOaGaeqyYdCNaaiykaiaacYhaaaa@4753@.
The phase spectrum will be plotted for angles in the principle range
−π≤∢X(ω)≤π
MathType@MTEF@5@5@+=feaafeart1ev1aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVeYdOipfYlH8qipiY=Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciGacaGaaeaabaWaaeaaeaaakeaacqGHsislcqaHapaCcqGHKjYOcqWIIiYucaWGybGaaiikaiabeM8a3jaacMcacqGHKjYOcqaHapaCaaa@433C@,
and the choice between
−π
MathType@MTEF@5@5@+=feaafeart1ev1aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVeYdOipfYlH8qipiY=Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciGacaGaaeaabaWaaeaaeaaakeaacqGHsislcqaHapaCaaa@38EA@ and
π
MathType@MTEF@5@5@+=feaafeart1ev1aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVeYdOipfYlH8qipiY=Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciGacaGaaeaabaWaaeaaeaaakeaacqaHapaCaaa@37FD@ will be made so that
∢X(−ω)=−∢X(ω)
MathType@MTEF@5@5@+=feaafeart1ev1aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVeYdOipfYlH8qipiY=Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciGacaGaaeaabaWaaeaaeaaakeaacqWIIiYucaWGybGaaiikaiabgkHiTiabeM8a3jaacMcacqGH9aqpcqGHsislcqWIIiYucaWGybGaaiikaiabeM8a3jaacMcaaaa@4376@,
for
ω≠0
MathType@MTEF@5@5@+=feaafeart1ev1aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVeYdOipfYlH8qipiY=Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciGacaGaaeaabaWaaeaaeaaakeaacqaHjpWDcqGHGjsUcaaIWaaaaa@3A8E@.
That is, the phase spectrum will be shown as an odd function of frequency,
except that
∢X(0)
MathType@MTEF@5@5@+=feaafeart1ev1aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVeYdOipfYlH8qipiY=Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciGacaGaaeaabaWaaeaaeaaakeaacqWIIiYucaWGybGaaiikaiaaicdacaGGPaaaaa@3A58@ might not be zero.
For
a number of signals of interest, the Fourier transform integral does not
converge in the usual sense of elementary calculus. Some of these signals can
be treated in a consistent fashion by admitting Fourier transforms that contain
so-called generalized functions. For example, if
x(t)=u(t)
MathType@MTEF@5@5@+=feaafeart1ev1aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVeYdOipfYlH8qipiY=Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciGacaGaaeaabaWaaeaaeaaakeaacaWG4bGaaiikaiaadshacaGGPaGaeyypa0JaamyDaiaacIcacaWG0bGaaiykaaaa@3DE1@,
the unit-step signal, then
where
δ(ω)
MathType@MTEF@5@5@+=feaafeart1ev1aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVeYdOipfYlH8qipiY=Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciGacaGaaeaabaWaaeaaeaaakeaacqaH0oazcaGGOaGaeqyYdCNaaiykaaaa@3B0B@ is the unit
impulse. For such a Fourier transform, we treat impulse components as
separate in computing the magnitude spectrum since an impulse is zero at all
values of
ω
MathType@MTEF@5@5@+=feaafeart1ev1aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVeYdOipfYlH8qipiY=Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciGacaGaaeaabaWaaeaaeaaakeaacqaHjpWDaaa@380D@ but one, though admittedly something very
special happens at that one point. Thus for the unit-step example,
In
plotting the magnitude spectrum, we indicate the impulse term using an arrow.
For the phase spectrum display, we ignore any impulse term, which contributes
angle, the angle of the “area” of the impulse, at only one value of
ω
MathType@MTEF@5@5@+=feaafeart1ev1aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVeYdOipfYlH8qipiY=Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciGacaGaaeaabaWaaeaaeaaakeaacqaHjpWDaaa@380D@.
Thus for the unit-step signal the phase spectrum is given by
The
applet below illustrates properties of the magnitude and phase spectra of
signals, and the effect on the spectra of typical operations on signals. Select
a signal from the provided signals, and the corresponding magnitude and phase
spectra will be displayed, both in mathematical terms and graphically. Then
select an operation and the resulting signal and its spectra are displayed.
Note
that impulses are shown as arrows, but the area is not indicated. Also,
amplitude scaling an impulse should be interpreted as area scaling. Finally,
the cosine pulse is chosen so that the pulse begins and ends at a zero crossing
of the cosine.
For
each signal, you can select an operation and the effects of the operation on
the signal and its spectra are displayed, both graphically and in terms of
analytical expressions. The available operations are described in the table
below.
and,
if
X(ω)
MathType@MTEF@5@5@+=feaafeart1ev1aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVeYdOipfYlH8qipiY=Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciGacaGaaeaabaWaaeaaeaaakeaacaWGybGaaiikaiabeM8a3jaacMcaaaa@3A43@ is an ordinary function that is continuous at
ω=0
MathType@MTEF@5@5@+=feaafeart1ev1aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVeYdOipfYlH8qipiY=Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciGacaGaaeaabaWaaeaaeaaakeaacqaHjpWDcqGH9aqpcaaIWaaaaa@39CD@,
For example, the time shifted unit-step signal,
u(t−T)
MathType@MTEF@5@5@+=feaafeart1ev1aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVeYdOipfYlH8qipiY=Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciGacaGaaeaabaWaaeaaeaaakeaacaWG1bGaaiikaiaadshacqGHsislcaWGubGaaiykaaaa@3B52@,
has the Fourier transform
Furthermore, derivatives of discontinuous signals
must be interpreted in the generalized sense. For example, the derivative of
the unit step is the unit impulse, and the corresponding transform operation gives
(An impulse of zero area is interpreted as no
impulse.)
The derivative of an impulse is a “doublet.” This
generalized signal is shown as an up/down arrow, but the mathematical
properties of doublets are beyond our scope. Also, the running-integral
operation on a signal typically yields a signal that has generalized functions
in its Fourier transform. As an important example, the running integral of a
unit step is a unit ramp, a signal whose transform involves a doublet.
Pick a signal type:
Pick a signal operation:
Exercises
For the tent signal,
which of the operations diminish the low-frequency content relative to the
high-frequency content of the signal? That is, which operations broaden
the magnitude spectrum? Can you explain your observations mathematically?
Time scaling by
a>0
MathType@MTEF@5@5@+=feaafeart1ev1aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVeYdOipfYlH8qipiY=Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciGacaGaaeaabaWaaeaaeaaakeaacaWGHbGaeyOpa4JaaGimaaaa@38E8@ leaves a unit-step function unchanged.
Verify this mathematically by showing that the Fourier transform of the
step is unchanged, using the time scaling property.
Verify the displayed
magnitude spectrum for the time derivative of the exponential signal. Note
the product rule gives the generalized derivative
·How do you distinguish between the time reversal
and the amplitude reversal (amplitude scale by
−1
MathType@MTEF@5@5@+=feaafeart1ev1aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVeYdOipfYlH8qipiY=Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciGacaGaaeaabaWaaeaaeaaakeaacqGHsislcaaIXaaaaa@37E8@ ) of a signal based on the resulting spectra?
(For example, beginning with
e−atu(t)
MathType@MTEF@5@5@+=feaafeart1ev1aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVeYdOipfYlH8qipiY=Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciGacaGaaeaabaWaaeaaeaaakeaacaaMe8UaamyzamaaCaaaleqabaGaeyOeI0IaamyyaiaadshaaaGccaWG1bGaaiikaiaadshacaGGPaaaaa@3F06@ consider the spectra of
eatu(−t)
MathType@MTEF@5@5@+=feaafeart1ev1aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVeYdOipfYlH8qipiY=Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciGacaGaaeaabaWaaeaaeaaakeaacaaMe8UaamyzamaaCaaaleqabaGaamyyaiaadshaaaGccaWG1bGaaiikaiabgkHiTiaadshacaGGPaaaaa@3F06@ and
−e−atu(t)
MathType@MTEF@5@5@+=feaafeart1ev1aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVeYdOipfYlH8qipiY=Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciGacaGaaeaabaWaaeaaeaaakeaacqGHsislcaWGLbWaaWbaaSqabeaacqGHsislcaWGHbGaamiDaaaakiaadwhacaGGOaGaamiDaiaacMcaaaa@3E66@.)