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Timevarying Systems
Timevarying distributed systems have not been examined in any detail in the scattering simulation literature, though timevarying WDFs [177] and DWNs [166] have both been proposed, with a focus on vocal tract modelling. Though it is true that timevariations in material parameters generally render a system nonpassive, we will show here how passive network representations may be developed for an important class of systems.
Consider a system of the form

(6.8) 
which is a simple generalization of the D symmetric hyperbolic form (3.1) to the case where and depend on both the spatial coordinates and time ; is assumed to be positive definite for all values of these coordinates and smoothlyvarying. The matrices
are again assumed to be constant and symmetric, and is not required to have any particular structure. It is easy to show that in this form, it is not possible to arrive immediately at an energy condition such as (3.5). In order to put system (6.8) into more useful form, note that we can factor as =
where
is some left matrix square root of . We can then rewrite (6.8) as
Now introduce a new dependent variable defined by
, where
and is assumed differentiable. Then, in terms of the new variable , we have
with
. Assuming that this source term is zero, we can then take the inner product of this expression with
to get
where
If is positive semidefinite, then integrating over
gives the energy condition
which is identical to the condition derived in §3.2, under the replacement of with . As long as and the time derivative of are bounded, it is always possible to make a choice of such that is positive semidefinite. For instance, we can choose
, with
where
signifies ``minimum eigenvalue of.'' Here, we essentially have a passivity condition in an exponentiallyweighted norm.
Consider a generalization of the sourcefree (1+1)D transmission line system,

(6.9a) 
where , , and , are all smooth positive functions of and . Introducing the variables
where is a positive constant as well as the scaled time variable
, and transformed coordinates as per (3.18), we can rewrite this system as
with
and
Under the choices
where now we have
then and are nonnegative, and the terms involving them can be interpreted as voltages across passive inductors, if powernormalized waves are employed (see §3.5.1 for more information on this definition of inductors). If we also choose

(6.10) 
then and are nonnegative and can be interpreted as passive resistances. The resulting MDKC is shown in Figure 6.4; an MDWD network can be immediately obtained through the methods discussed in Chapter 3, or network manipulations and alternative integration rules may be employed to get a DWN. A balanced form (see §3.12) is also possible, and gives a less strict bound on , but the bound on
remains unchanged.
Figure 6.4:
MDKC for timevarying (1+1)D transmission line system (6.9). The exponential weighting of the current variables can be viewed (formally) as a timevarying transformer coupling.

A direct application of this MDKC to an important music synthesis problem would be the simulation of acoustic wave propagation in the vocal tract, under timevarying conditions. Such a system of PDEs is mentioned in [145], and has the exact form of (6.9), with , and under the replacements
where is the air density, is the speed of sound, is the surface area of the tube, is the volume velocity and is the pressure variation. The condition (6.10) then reduces to
If the time variation in is slow, then
will be close to zero, and the exponential weighting will not be overly severe. The problems, for realtime synthesis applications, are that we will need to have an a priori estimate of the maximal time variation of the vocal tract area, and that we will apply an exponential weighting to the signal output from the scattering simulation. This exponential weighting may be viewed as a passive operation involving timevarying transformers (as shown in Figure 6.4).
Next: Afterword
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Stefan Bilbao
20020122