Orthogonal Two-Channel Filter Banks

Recall the reconstruction equation for the two-channel, critically sampled, perfect-reconstruction filter-bank:

\hat{X}(z) &=& \frac{1}{2}[H_0(z)F_0(z) + H_1(z)F_1(z)]X(z)
...\\ [0.1in]
&+& \frac{1}{2}[H_0(-z)F_0(z) + H_1(-z)F_1(z)]X(-z)

This can be written in matrix form as

$\displaystyle \hat{X}(z) = \frac{1}{2} \left[\begin{array}{c} F_0(z) \\ [2pt] F...
\left[\begin{array}{c} X(z) \\ [2pt] X(-z) \end{array}\right]

where the above $ 2 \times 2$ matrix, $ \bold{H}_m(z)$, is called the alias component matrix (or analysis modulation matrix). If

$\displaystyle {\tilde {\bold{H}}}_m(z)\bold{H}_m(z) = 2\bold{I}

where $ {\tilde {\bold{H}}}_m(z)\isdef \bold{H}_m^T(z^{-1})$ denotes the paraconjugate of $ \bold{H}_m(z)$, then the alias component (AC) matrix is lossless, and the (real) filter bank is orthogonal.

It turns out orthogonal filter banks give perfect reconstruction filter banks for any number of channels. Orthogonal filter banks are also called paraunitary filter banks, which we'll study in polyphase form in §10.5 below. The AC matrix is paraunitary if and only if the polyphase matrix (defined in the next section) is paraunitary [266].

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Simple Examples of Perfect Reconstruction
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Conjugate Quadrature Filters (CQF)