Analytic Signals and Hilbert Transform Filters

A signal which has no negative-frequency components is called an analytic signal.^4.12 Therefore, in continuous time, every analytic signal can be represented as

$\displaystyle z(t) = \frac{1}{2\pi}\int_0^{\infty} Z(\omega)e^{j\omega t}d\omega$

where $Z(\omega)$ is the complex coefficient (setting the amplitude and phase) of the positive-frequency complex sinusoid $\exp(j\omega t)$ at frequency $\omega$ .

Any real sinusoid $A\cos(\omega t + \phi)$ may be converted to a positive-frequency complex sinusoid $A\exp[j(\omega t + \phi)]$ by simply generating a phase-quadrature component $A\sin(\omega t + \phi)$ to serve as the ``imaginary part'':

$\displaystyle A e^{j(\omega t + \phi)} = A\cos(\omega t + \phi) + j A\sin(\omega t + \phi)$

The phase-quadrature component can be generated from the in-phase component by a simple quarter-cycle time shift.^4.13

For more complicated signals which are expressible as a sum of many sinusoids, a filter can be constructed which shifts each sinusoidal component by a quarter cycle. This is called a Hilbert transform filter. Let ${\cal H}_t\{x\}$ denote the output at time of the Hilbert-transform filter applied to the signal . Ideally, this filter has magnitude at all frequencies and introduces a phase shift of $-\pi/2$ at each positive frequency and $+\pi/2$ at each negative frequency. When a real signal and its Hilbert transform $y(t) = {\cal H}_t\{x\}$ are used to form a new complex signal , the signal is the (complex) analytic signal corresponding to the real signal . In other words, for any real signal , the corresponding analytic signal $z(t)=x(t) + j {\cal H}_t\{x\}$ has the property that all ``negative frequencies'' of have been ``filtered out.''

To see how this works, recall that these phase shifts can be impressed on a complex sinusoid by multiplying it by $\exp(\pm j\pi/2) = \pm j$ . Consider the positive and negative frequency components at the particular frequency $\omega_0$ :

$\begin{eqnarray*} x_+(t) &\isdef & e^{j\omega_0 t} \\ x_-(t) &\isdef & e^{-j\omega_0 t} \end{eqnarray*}$

Now let's apply a degrees phase shift to the positive-frequency component, and a degrees phase shift to the negative-frequency component:

$\begin{eqnarray*} y_+(t) &=& e^{-j\pi/2} e^{j\omega_0 t} = -j e^{j\omega_0 t} \\ y_-(t) &=& e^{j\pi/2} e^{-j\omega_0 t} = j e^{-j\omega_0 t} \end{eqnarray*}$

Adding them together gives

$\begin{eqnarray*} z_+(t) &\isdef & x_+(t) + j y_+(t) = e^{j\omega_0 t} - j^2 e^{... ... x_-(t) + j y_-(t) = e^{-j\omega_0 t} + j^2 e^{-j\omega_0 t} = 0 \end{eqnarray*}$

and sure enough, the negative frequency component is filtered out. (There is also a gain of 2 at positive frequencies.)

For a concrete example, let's start with the real sinusoid

$\displaystyle x(t)=2\cos(\omega_0 t) = e^{j\omega_0 t} + e^{-j\omega_0 t}.$

Applying the ideal phase shifts, the Hilbert transform is

$\begin{eqnarray*} y(t) &=& e^{j\omega_0 t-j\pi/2} + e^{-j\omega_0 t + j\pi/2}\\ &=& -je^{j\omega_0 t} + je^{-j\omega_0 t} = 2\sin(\omega_0 t). \end{eqnarray*}$

The analytic signal is then

$\displaystyle z(t) = x(t) + j y(t) = 2\cos(\omega_0 t) + j 2\sin(\omega_0 t) = 2 e^{j\omega_0 t},$

by Euler's identity. Thus, in the sum

, the negative-frequency components of

and

cancel out, leaving only the positive-frequency component. This happens for any real signal

, not just for sinusoids as in our example.

**Figure 4.16:** Creation of the analytic signal $z(t)=e^{j\omega _0 t}$ from the real sinusoid $x(t) = \cos(\omega_0 t)$ and the derived phase-quadrature sinusoid $y(t) = \sin(\omega_0 t)$ , viewed in the frequency domain. a) Spectrum of . b) Spectrum of . c) Spectrum of . d) Spectrum of .
$\includegraphics[width=2.8in]{eps/sineFD}$

Figure 4.16 illustrates what is going on in the frequency domain. At the top is a graph of the spectrum of the sinusoid $\cos(\omega_0 t)$ consisting of impulses at frequencies $\omega=\pm\omega_0$ and zero at all other frequencies (since $\cos(\omega_0 t) = (1/2)\exp(j\omega_0 t) + (1/2)\exp(-j\omega_0 t)$ ). Each impulse amplitude is equal to . (The amplitude of an impulse is its algebraic area.) Similarly, since $\sin(\omega_0 t) = (1/2j)\exp(j\omega_0 t) - (1/2j)\exp(-j\omega_0 t) = -(j/2) \exp(j\omega_0 t) + (j/2)\exp(-j\omega_0 t)$ , the spectrum of $\sin(\omega_0 t)$ is an impulse of amplitude at $\omega=\omega_0$ and amplitude at $\omega=-\omega_0$ . Multiplying by results in $j\sin(\omega_0 t) = (1/2)\exp(j\omega_0 t) - (1/2)\exp(-j\omega_0 t)$ which is shown in the third plot, Fig.4.16c. Finally, adding together the first and third plots, corresponding to , we see that the two positive-frequency impulses add in phase to give a unit impulse (corresponding to $\exp(j\omega_0 t)$ ), and at frequency $-\omega_0$ , the two impulses, having opposite sign, cancel in the sum, thus creating an analytic signal , as shown in Fig.4.16d. This sequence of operations illustrates how the negative-frequency component $\exp(-j\omega_0 t)$ gets filtered out by summing $\cos(\omega_0 t)$ with $j\sin(\omega_0 t)$ to produce the analytic signal $\exp(j\omega_0 t)$ corresponding to the real signal $\cos(\omega_0 t)$ .

As a final example (and application), let $x(t) = A(t)\cos(\omega t)$ , where is a slowly varying amplitude envelope (slow compared with $\omega$ ). This is an example of amplitude modulation applied to a sinusoid at ``carrier frequency'' $\omega$ (which is where you tune your AM radio). The Hilbert transform is very close to $y(t)\approx A(t)\sin(\omega t)$ (if were constant, this would be exact), and the analytic signal is $z(t)\approx A(t)e^{j\omega t}$ . Note that AM demodulation^4.14is now nothing more than the absolute value. I.e., $A(t) = \left\vert z(t)\right\vert$ . Due to this simplicity, Hilbert transforms are sometimes used in making amplitude envelope followers for narrowband signals (i.e., signals with all energy centered about a single ``carrier'' frequency). AM demodulation is one application of a narrowband envelope follower.