Paraunitary systems are essentially multi-input, multi-output (MIMO) allpass filters. Let denote the matrix transfer function of a paraunitary system. In the square case ( ), the matrix determinant, , is an allpass filter. Therefore, if a square contains FIR elements, its determinant is a simple delay: for some integer .
An -channel analysis filter bank can be viewed as an MIMO filter:
A paraunitary filter bank must therefore satisfy
More generally, we allow paraunitary filter banks to scale and/or delay the input signal:
where is some nonnegative integer and .
We can note the following properties of paraunitary filter banks:
- The synthesis filter bank is simply the paraconjugate of the
analysis filter bank:
That is, since the paraconjugate is the inverse of a paraunitary filter matrix, it is exactly what we need for perfect reconstruction.
- The channel filters
are power complementary:
This follows immediately from looking at the paraunitary property on the unit circle.
is FIR, the corresponding synthesis filter matrix
is also FIR.
is FIR, each synthesis filter,
, is simply the
of its corresponding
where is the filter length. (When the filter coefficients are complex, includes a complex conjugation as well.) This follows from the fact that paraconjugating an FIR filter amounts to simply flipping (and conjugating) its coefficients. As we observed in (11.83) above (§11.5.2), only trivial FIR filters of the form can be paraunitary in the single-input, single-output (SISO) case. In the MIMO case, on the other hand, paraunitary systems can be composed of FIR filters of any order.
- FIR analysis and synthesis filters in paraunitary filter banks
have the same amplitude response. This follows from the fact
, i.e., flipping an FIR filter
conjugates the frequency response, which does
not affect its amplitude response
- The polyphase matrix
for any FIR paraunitary perfect
reconstruction filter bank can be written as the product of a
paraunitary and a unimodular matrix, where a
unimodular polynomial matrix
is any square
polynomial matrix having a constant nonzero
determinant. For example,
Lossless Filter Examples