In addition to the sinusoidal and exponential signals discussed in the previous
lecture, other important basic signals are the unit step and unit impulse. In
this lecture, we discuss these signals and then proceed to a discussion of sys-
tems, first in general and then in terms of various classes of systems defined
by specific system properties.
The unit step, both for continuous and discrete time, is zero for negative
time and unity for positive time. In discrete time the unit step is a well-defined
sequence, whereas in continuous time there is the mathematical complication
of a discontinuity at the origin. A similar distinction applies to the unit im-
pulse. In discrete time the unit impulse is simply a sequence that is zero ex-
cept at n = 0, where it is unity. In continuous time, it is somewhat badly be-
haved mathematically, being of infinite height and zero width but having a
finite area.
The unit step and unit impulse are closely related. In discrete time the
unit impulse is the first difference of the unit step, and the unit step is the run-
ning sum of the unit impulse. Correspondingly, in continuous time the unit im-
pulse is the derivative of the unit step, and the unit step is the running integral
of the impulse. As stressed in the lecture, the fact that it is a first difference
and a running sum that relate the step and the impulse in discrete time and a
derivative and running integral that relate them in continuous time should not
be misinterpreted to mean that a first difference is a good "representation" of
a derivative or that a running sum is a good "representation" of a running inte-
gral. Rather, for this particular situation those operations play corresponding
roles in continuous time and in discrete time.
As indicated above, there are a variety of mathematical difficulties with
the continuous-time unit step and unit impulse that we do not attempt to ad-
dress carefully in these lectures. This topic is treated formally mathematically
through the use of what are referred to as generalized functions, which is a
level of formalism well beyond what we require for our purposes. The essen-
tial idea, however, as discussed in Section 3.7 of the text, is that the important
aspect of these functions, in particular of the impulse, is not what its value is
at each instant of time but how it behaves under integration.
In this lecture we also introduce systems. In their most general form, sys-
tems are hard to deal with analytically because they have no particular prop-
erties to exploit. In other words, general systems are simply too general. We
define, discuss, and illustrate a number of system properties that we will find
useful to refer to and exploit as the lectures proceed, among them memory,
invertibility, causality, stability, time invariance, and linearity. The last two,
linearity and time invariance, become particularly significant from this point
on. Somewhat amazingly, as we'll see, simply knowing that a system is linear
and time-invariant affords us an incredibly powerful array of tools for analyz-
ing and representing it. While not all systems have these properties, many do,
and those that do are often easiest to understand and implement. Consequent-
ly, both continuous-time and discrete-time systems that are linear and time-
invariant become extremely significant in system design, implementation, and
analysis in a broad array of applications.