Passive Reflectances
From (L.19),
we have that the reflectance seen at a continuous-time impedance
is given for force waves by
where

is the
wave impedance connected to the
impedance 
.
As discussed earlier, all passive impedances are
positive real.
It can be easily verified that

positive real implies that

is stable and has magnitude less than or equal to

on the

axis (and hence over the entire left-half plane, by the
maximum modulus
theorem),
i.e.,

re
Any stable

satisfying (
M.1) is called a
passive
reflectance.
Solving for
, we can characterize every passive impedance in terms
of its corresponding reflectance:
The reflectance is always defined relative to an impedance

which is
the impedance attached to

to create an
impedance discontinuity and
thereby generate (frequency-dependent) reflections.
In the discrete-time case, we have the same basic relations, but in the
plane:
and
Stable functions

satisfying (
M.1) are also known in the
mathematics literature as
Schur functions. In the limit as damping
goes to zero (all
poles of

converge to the unit circle, with
interlacing zeros as required to remain positive real), the reflectance
approaches the
transfer function of an
allpass filter. Thus, the
Schur function is a generalization of an
allpass transfer function to allow
for loss. Recalling that a lossless impedance is called a
reactance,
we can say that every reactance gives rise to an allpass reflectance.
Thus, for example, waves reflecting off a
mass at the end of the string
will be allpass
filtered. It is intuitively very straightforward that the
reflection magnitude cannot exceed

at any frequency when reflecting
from a passive impedance back into a passive medium at impedance

. It
is also intuitively satisfying that lossless reflection involves only a
phase shift and no amplification or attenuation at any frequency.
Previous:
Passive ImpedancesNext:
Passive String Terminations
written by Julius Orion Smith III
Julius Smith's background is in electrical engineering (BS Rice 1975, PhD Stanford 1983). He is presently Professor of Music and Associate Professor (by courtesy) of Electrical Engineering at
Stanford's Center for Computer Research in Music and Acoustics (CCRMA), teaching courses and pursuing research related to signal processing applied to music and audio systems. See
http://ccrma.stanford.edu/~jos/ for details.