Multi-Input, Multi-Output (MIMO)
Allpass Filters
To generalize lossless filters to the multi-input, multi-output (MIMO) case, we must generalize conjugation to MIMO transfer function matrices:
Theorem: A
transfer function matrix
is
lossless if and only if
its frequency-response matrix
is unitary, i.e.,
for all
Let
denote the length
output vector at time
, and
let
denote the input
-vector at time
. Then in the
frequency domain we have
, which
implies
We have thus shown that in the MIMO case, losslessness is equivalent to having a unitary frequency-response matrix. A MIMO allpass filter is therefore any filter with a unitary frequency-response matrix.
Note that
is a
matrix product
of a
times a
matrix. If
, then the rank
must be deficient. Therefore,
. (There must be at least as
many outputs as there are inputs, but it's ok to have extra outputs.)
Paraunitary MIMO Filters
In §C.2, we generalized the allpass property
to the entire complex plane as
MIMO Paraconjugate
Definition:
The paraconjugate of
is defined as
MIMO Paraunitary Condition
With the above definition for paraconjugation of a MIMO transfer-function
matrix, we may generalize the MIMO allpass condition Eq.
(C.2) to the
entire
plane as follows:
Theorem:
Every lossless
transfer function matrix
is paraunitary,
i.e.,
By construction, every paraunitary matrix transfer function is
unitary on the unit circle for all
. Away from the
unit circle, the paraconjugate
is the unique analytic
continuation of
(the Hermitian transpose of
).
Example:
The normalized DFT matrix is an
order zero
paraunitary transformation. This is because the normalized DFT
matrix,
, where
, is a
unitary matrix:
Properties of Paraunitary Systems
Paraunitary systems are essentially multi-input, multi-output (MIMO)
allpass filters. Let
denote the
matrix transfer
function of a paraunitary system. Some of its properties include the
following [98]:
- 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
.
Properties of Paraunitary Filter Banks
An
-channel filter bank can be viewed as an
MIMO filter
A paraunitary filter bank must therefore obey
We can note the following properties of paraunitary filter banks:
- A synthesis filter bank
corresponding
to analysis filter bank
is defined as that filter bank
which inverts the analysis filter bank, i.e., satisfies
Clearly, not every filter bank will be invertible in this way. When it is, it may be called a perfect reconstruction filter bank. When a filter bank transfer function
is paraunitary, its
corresponding synthesis filter bank is simply the paraconjugate filter
bank
, or
- The channel filters
in a paraunitary filter bank
are power complementary:
This follows immediately from looking at the paraunitary property on the unit circle.
- When
is FIR, the corresponding synthesis filter
matrix
is also FIR. Note that this implies an FIR
filter-matrix can be inverted by another FIR filter-matrix. This is in
stark contrast to the case of single-input, single-output FIR filters,
which must be inverted by IIR filters, in general.
- When
is FIR, each synthesis filter,
, is simply the
of its corresponding
analysis filter
:
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.
Note that only trivial FIR filters 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 that
, i.e., flipping an FIR filter impulse response
conjugates the frequency response, which does not affect its amplitude
response
.
Paraunitary Filter Examples
The Haar filter bank is defined as
For more about paraunitary filter banks, see Chapter 6 of [98].
Next Section:
Allpass Problems
Previous Section:
Paraunitary FiltersC.4







