Next  |  Prev  |  Up  |  Top  |  Index  |  JOS Index  |  JOS Pubs  |  JOS Home  |  Search

Primer on Hilbert Transform Theory

We need a Hilbert-transform filter $ {\cal H}$ to compute the imaginary part $ y(t)$ of the analytic signal $ x_a(t)$ given its real part $ x(t)$ . That is,

$\displaystyle x_a(t) \eqsp x(t) + j\,y(t)$ (5.14)

where $ y = {\cal H}\{x\}$ . In the frequency domain, we have

$\displaystyle X_a(\omega) \eqsp X(\omega) + j\,Y(\omega) \eqsp \left[1+j\,H(\omega)\right]\,X(\omega)$ (5.15)

where $ H(\omega)$ denotes the frequency response of the Hilbert transform $ {\cal H}$ . Since by definition we have $ X_a(\omega)=0$ for $ \omega<0$ , we must have $ j\,H(\omega)=-1$ for $ \omega<0$ , so that $ H(\omega)=j$ for negative frequencies (an allpass response with phase-shift $ +90$ degrees). To pass the positive-frequency components unchanged, we would most naturally define $ H(\omega)=0$ for $ \omega>0$ . However, conventionally, the positive-frequency Hilbert-transform frequency response is defined more symmetrically as $ H(\omega)=-j$ for $ \omega>0$ , which gives $ j\,H(\omega)=+1$ and $\mbox{re\ensuremath{\left\{X_a(\omega)\right\}}}=2X(\omega)$ , i.e., the positive-frequency components of $ X$ are multiplied by $ 2$ .

In view of the foregoing, the frequency response of the ideal Hilbert-transform filter may be defined as follows:

$\displaystyle H(\omega) \isdefs \left\{\begin{array}{ll} \quad\! j, & \omega<0 \\ [5pt] \quad\!0, & \omega=0 \\ [5pt] -j, & \omega>0 \\ \end{array} \right. \protect$ (5.16)

Note that the point at $ \omega
= 0$ can be defined arbitrarily since the inverse-Fourier transform integral is not affected by a single finite point (being a ``set of measure zero'').

The ideal filter impulse response $ h(n)$ is obtained by finding the inverse Fourier transform of (4.16). For discrete time, we may take the inverse DTFT of (4.16) to obtain the ideal discrete-time Hilbert-transform impulse response, as pursued in Problem 10. We will work with the usual continuous-time limit $ h(t)=1/(\pi t)$ in the next section.

Next  |  Prev  |  Up  |  Top  |  Index  |  JOS Index  |  JOS Pubs  |  JOS Home  |  Search

[How to cite this work]  [Order a printed hardcopy]  [Comment on this page via email]
[Watch the Video]  [Work some Exercises]  [Examination]  
``Spectral Audio Signal Processing'', by Julius O. Smith III, W3K Publishing, 2011, ISBN 978-0-9745607-3-1.
Copyright © 2015-02-01 by Julius O. Smith III
Center for Computer Research in Music and Acoustics (CCRMA),   Stanford University