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 , where denotes the identity matrix, and denotes the Hermitian transpose (complex-conjugate transpose) of :
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
- The channel filters in a paraunitary filter bank
are power complementary:
- 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
:
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].
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Allpass Problems
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Paraunitary FiltersC.4