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Introduction
The digital waveguide (DW) method has been used for many years to
provide highly efficient algorithms for musical sound synthesis based
on physical models [24,29]. For a much longer time,
finite-difference time-domain (FDTD) schemes have been used to
simulate more general situations at generally higher cost
[23,4,5,2].
In recent years, there has been interest in relating these methods to
each other [7] and in combining them for more
general simulations. For example, modular hybrid methods have been
devised which interconnect DW and FDTD simulations by means of a
KW converter [13,15]. The basic idea
of the KW-converter adaptor is to convert the ``Kirchhoff variables'' of the
FDTD, such as string displacement, velocity, etc., to ``wave
variables'' of the DW. The W variables are regarded as the
traveling-wave components of the K variables.
In this paper, we present an alternative to the KW converter. Instead of
converting K variables to W variables, or vice versa, in the time
domain, conversion formulas are derived with respect to the current
state as a function of spatial coordinates. As a result, it becomes
simple to convert any instantaneous state configuration from FDTD to
DW form, or vice versa. Thus, instead of providing the necessary
time-domain filter to implement a KW converter converting traveling-wave
components to physical displacement of a vibrating string, say, one
may alternatively set the displacement variables instantaneously to
the values corresponding to a given set of traveling-wave components
in the string model. Another benefit of the formulation is an exact
physical interpretation of arbitrary initial conditions and
excitations in the K-variable FDTD method. Since the DW formulation
is exact in principle (though bandlimited), while the FDTD is
approximate, even in principle, it can be argued that the true
physical interpretation of the FDTD method is that given by the DW
method. Since both methods generate the same evolution of state from
a common starting point, they may only differ in computational
expense, numerical sensitivity, and in the details of supplying
initial conditions and boundary conditions.
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