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Spectral factorization

A causal function is one that vanishes at negative time. Too short a summary is to say the exponential of a causal is a causal. What is meant is if we take the Fourier transformation of a causal function, exponentiate it, and then inverse transform we will again have a causal function. This is the heart of spectral factorization, an obscure mathematical calculation addressing interesting practical applications.

Start with $ Z$ -transforms. Given a time function $ (1,u_1,u_2,u_3,\cdots)$ its $ Z$ -transform is $ U(Z) = 1 +u_1Z +u_2Z^2 +u_3Z^3+\cdots$ . When you identify $ Z=e^{i\omega\Delta t}$ and $ Z^5=e^{i\omega 5\Delta t}$ the $ Z$ -transform is clearly a Fourier series. An example of a causal function is $ u_\tau$ . It is causal because $ u_\tau=0$ for $ \tau<0$ likewise, $ U(Z)$ has no powers of $ 1/Z$ .

We may exponentiate $ U(Z)$ by a frequency domain method or a time domain method. Easiest is the frequency domain method. Write $ e^{U(Z(\omega))}$ for all $ \omega$ , then Fourier transform to time. More interesting is the time domain method. The polynomial U has no powers of $ 1/Z$ . The power series for an exponential is $ e^U= 1 + U + U^2/2! + U^3/3! +\cdots$ . Inserting the polynomial for U into the power series for $ e^U$ gives us a new polynomial (infinite series) that has no powers of $ 1/Z$ . Furthermore, this new polynomial always converges because of the powerful influence of the denominator factorials. Thus we have shown that the ``exponential of a causal is a causal''.

Let $ \bar{S}(Z(\omega))$ be an amplitude spectrum $ \bar S(\omega)>0$ with logarithm $ \bar U= \log \bar S$ . The exponential is the inverse of the logarithm

$\displaystyle \bar{S}$ $\displaystyle =$ $\displaystyle e^{\log \bar{S}} \ =\ e^{\bar U}$ (1)

Both $ \bar S$ and $ \bar U$ are real symmetric functions of $ \omega$ . In the time domain, $ \vert\bar S\vert^2$ corresponds to an autocorrelation. In the time domain, $ \bar U$ merely corresponds to a real symmetric function $ \bar u_\tau$ . Adding some phase function $ \Phi(\omega)$ to $ \bar U$ will shift the time function $ s_\tau$ , likely shifting each frequency differently.
$\displaystyle S$ $\displaystyle =$ $\displaystyle e^{\log \bar{S}+i\Phi} \ =\ e^{\bar U+i\Phi} \ =\ e^U$ (2)

Keeping $ \bar U$ fixed keeps the spectrum $ S^\ast S$ fixed. Let $ u_\tau$ now correspond to the Fourier transform of $ U(\omega)=\bar U+i\Phi$ . The time symmetric part of $ u_\tau$ corresponds to $ \bar U(\omega)$ while the antisymmetric part of $ u_\tau$ corresponds to the newly added phase $ \Phi(\omega)$ . How shall we choose $ \Phi(\omega)$ ? Let us choose the antisymmetric part of $ u_\tau$ instead, choose it to cancel the symmetric part of $ u_\tau$ on the negative $ \tau$ axis. In other words, let us choose $ u_\tau$ to be causal. Recalling that ``exponentials of causals are causal'' we have thus created a causal $ s_\tau$ . Hooray! Hooray because $ s_\tau$ has the same spectrum $ \bar S$ that we started with. We started with a spectrum $ \bar S$ and constructed a causal wavelet $ s_\tau$ with that spectrum. Good trick! This is called ``spectral factorization.'' Causal decon is simply taking your data $ D$ and dividing by a causal source waveform $ S$ .


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Next: Mostly causal decon Up: GETTING THE BEST OF Previous: GETTING THE BEST OF

2012-05-10