This first lecture is intended to broadly introduce the scope and direction of
the course. We are concerned, of course, with signals and with systems that
process signals. Signals can be categorized as either continuous-time signals,
for which the independent variable is a continuous variable, or discrete-time
signals, for which the independent variable is an integer. Examples of con-
tinuous-time signals include the sound pressure at a microphone as a function
of time or image brightness as a function of two spatial variables. In the first
case the signal is a one-dimensional signal, in the second a two-dimensional
signal. Common examples of discrete-time signals are economic time series,
such as the daily or weekly stock market index, antenna arrays, etc. While
these examples include both one-dimensional and two-dimensional signals,
our detailed discussions in this course focus only on one-dimensional signals.
Many of the general concepts and results, however, will be illustrated with
two-dimensional signals, specifically images.