Design and modeling are two generic tasks in which engineers participate after completing their undergraduate
degrees. In addition to preparation in mathematics for the other disciplines within electrical engineering,
there are additional areas in mathematics that are necessary to support learning and growth in
design and modeling. Such areas include statistics, empirical modeling, parameter estimation, system
identification, model validation and design of experiments. Demand from industry for expertise in these
areas appears to be much stronger than demand within electrical engineering curricula. That may explain
why these areas are not prerequisites for courses in electrical engineering. However, expertise in these
areas is increasingly important for electrical engineering graduates.
Topics from these areas that will be valuable for engineering graduates include the concept of a random
variable, analysis of sets of data, concepts of sample means, sample variances and other sample statistics
as random variables, and hypothesis testing. To illustrate why these topics are important here are some
examples of applications.
First Example, Simple Parameter Estimation: Construct a circuit containing a resistor (resistance = R)
and a capacitor (capacitance = C). If the capacitor is initially charged and then discharged through the circuit,
voltages and currents decay exponentially. Data on a particular voltage can be taken at various points
in time. Students then must estimate the time constant ( = RC) using the accumulated data. There are a
variety of techniques through which estimates of the time constant can be obtained. Students need to be
familiar with the techniques as well as the supporting concepts and broader applications.
Second Example, Design of Experiments: Design a feedback controller that meets several specifications
and minimizes percent overshoot. There are a number of parameters that may be adjusted. Students should
be able to design a set of experiments that will help determine narrow intervals for the parameter values
in order to optimize the design.