Introduction to Lumped Models
Bilinear Transformation
Finite Differences vs. the Bilinear TransformSearch Physical Audio Signal Processing
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Recall that the finite difference approximation (FDA) defines the
elementary differentiator by
(ignoring the
scale factor
for now) which approximates the ideal transfer
function
by
. The bilinear transform calls
instead for the transfer function
(again
dropping scale factors) which introduces a pole at
and gives
us the recursion
.
Note that this new pole is right on the unit circle and is therefore
undamped. Any signal energy at half the sampling rate will circulate
forever in the recursion, and due to round-off error, it will tend to
grow. This is therefore not a very useful improvement of the
differentiator. To get something really practical, we need to specify
that the filter frequency response approximate
over a
finite range of frequencies
, where
, above which we allow the response to ``roll off''
to zero. This is how we pose the differentiator problem in terms of
general purpose filter design (see §R.3) [371].
To understand the properties of the finite difference approximation in the
frequency domain, we may look at the properties of its
-plane
to
-plane mapping
Setting
to 1 for simplicity and solving the FDA mapping for z gives