Signals and Systems (EET4732C)

Course Description

Signals and Systems is the analytical keystone of an electronics engineering technology degree. Miami Dade College publishes EET4732C at 4 credits, prerequisite EET3716C, covering continuous-time signal and system analysis, the input-output relationships of linear time-invariant (LTI) systems, transient and steady-state analysis, frequency-domain and Fourier analysis, and the characterization of LTI systems using Laplace transforms.

Within the SCNS taxonomy, EET is the Electronic Engineering Technology prefix and the C suffix marks an integrated lecture-and-laboratory course. Contact hours are given here as 80, matching the published 4-credit EET4158C in the same programme and prerequisite chain.

Read the collision warning below before anything else in this guide. The unsuffixed number EET4732 denotes a different subject at Daytona State, and this is the sharpest number-versus-title trap in the EET prefix.

What the course actually does is teach you to stop thinking about circuits and start thinking about systems — a box with an input and an output whose behaviour is fully described by its impulse response or its transfer function, regardless of whether the box is made of resistors, mechanical linkages, or software. That abstraction is the reason the course exists, and it is what makes signal processing, communications, and control comprehensible afterwards.

Learning Outcomes

Required Outcomes

• Classify signals: continuous and discrete, periodic and aperiodic, energy and power, even and odd.
• Describe and use elementary signals, including the unit step, unit impulse, ramp, and complex exponential.
• Perform signal operations: time shifting, scaling, and reversal.
• Define linearity, time invariance, causality, memory, and stability and test systems for each.
• Describe an LTI system by its impulse response.
• Compute the convolution integral and interpret it graphically.
• Determine system response to arbitrary inputs using convolution.
• Analyze transient and steady-state response and separate the two.
• Represent periodic signals with the Fourier series in trigonometric and exponential form.
• Determine and interpret amplitude and phase spectra.
• Apply the Fourier transform to aperiodic signals and state its principal properties.
• Relate the frequency response of a system to its transfer function.
• Apply the Laplace transform to characterize LTI systems.
• Determine transfer functions, poles, and zeros and relate them to system behaviour.
• Assess stability from pole locations and the region of convergence.
• Describe filtering in the frequency domain and characterize ideal and practical filters.
• Describe bandwidth, and state the sampling theorem and the consequences of aliasing.
• Analyze systems using block diagrams and interconnection rules.
• Use computational tools to compute, plot, and verify signal and system behaviour.
• Verify system response experimentally and reconcile it with analysis.
• Report analysis and experimental work to professional technical standard.

Optional Outcomes

• Introduce discrete-time signals and the z-transform.
• Introduce the discrete Fourier transform and the FFT.
• Describe modulation and its frequency-domain interpretation.
• Describe state-space representation.
• Describe correlation and matched filtering.
• Describe random signals and noise at an introductory level.

Major Topics

Required Topics

• Signal classification
• Elementary signals: step, impulse, ramp, exponential
• Signal operations and transformations
• System properties: linearity, time invariance, causality, stability
• Impulse response
• Convolution
• Transient and steady-state response
• Fourier series
• Amplitude and phase spectra
• The Fourier transform and its properties
• Frequency response
• The Laplace transform and system characterization
• Transfer functions, poles, and zeros
• Stability and region of convergence
• Filtering and filter characteristics
• Bandwidth, sampling, and aliasing
• Block diagrams and system interconnection
• Computational analysis and plotting
• Laboratory verification
• Technical reporting

Optional Topics

• Discrete-time signals and the z-transform
• DFT and FFT
• Modulation
• State-space representation
• Correlation and matched filtering
• Random signals and noise

Resources & Tools

• Signals and Systems (Oppenheim, Willsky & Nawab) — the canonical text; demanding, and the reference the field is written against.
• Signals and Systems (Haykin & Van Veen) — a more approachable standard, often the better first read.
• Schaum's Outline of Signals and Systems — inexpensive, and dense with the worked problems this course requires.
• MATLAB with the Signal Processing Toolbox — the industry standard; check your college's licence before purchasing.
• Python with NumPy, SciPy, and Matplotlib — free, fully capable for everything in this course, and the more portable skill. GNU Octave is a free MATLAB-syntax alternative.
• Jupyter notebooks — free, and unusually well suited to this material because you can plot a signal, transform it, and plot the result in one document.
• Brian Douglas on YouTube — free, and the clearest available explanations of transfer functions, poles and zeros, and frequency response.
• MIT OpenCourseWare 6.003 "Signals and Systems" — free, complete, and taught by the authors of the standard text.
• Julius Smith's online books (CCRMA, Stanford) — free, and excellent on Fourier and filtering with an intuitive slant.
• GNU Radio — free; with an inexpensive RTL-SDR dongle it turns abstract spectra into things you can see and hear.

Career Pathways

• Signal processing technologist — the direct application; SOC 17-3023.
• Communications and RF engineering technology — modulation, bandwidth, and filtering are this course applied.
• Radar and electronic warfare — a major Florida employment area; L3Harris (Palm Bay/Melbourne), Lockheed Martin (Orlando), Northrop Grumman, and Raytheon recruit heavily for exactly this background, and security clearances raise pay substantially.
• Audio and acoustics — filtering, spectra, and convolution are the working vocabulary.
• Biomedical instrumentation — ECG, EEG, and imaging are signal processing problems.
• Control systems — the transfer-function machinery is shared; see the companion course note below.
• Test and measurement engineering.
• Embedded DSP development — at Miami Dade this course is a prerequisite for CET4190C Applied Digital Signal Processing.
• Space Coast launch and payload operations — telemetry and communications work.

Special Information

⚠⚠ Number collision: EET4732C is not EET4732 — and they are different subjects

The most consequential fact in this guide, and one of the sharpest number-versus-title traps documented in this repository.

• Miami Dade College: EET4732C = "Signals and Systems," 4 credits, prerequisite EET3716C.
• Daytona State College: EET4732 (no suffix) = "Feedback Control Systems," 3 credits, prerequisites EET3716 and PHY2048C or ETG3541, with a corequisite laboratory EET4732L. Its published description is unmistakably control theory: "time and frequency domain modeling; analysis of networks and control systems; time response; block diagram reduction, Bode plots, root locus, stability, compensation considerations, and digital simulation techniques."
• Miami Dade uses a separate number for feedback control: EET4730C "Feedback Control Systems," 4 credits, also prerequisite EET3716C. So at one institution 4732 means signals and systems and 4730 means control; at the other, 4732 means control.
• Valencia adds a third variant: EET3732 "Linear Control Systems," 3 credits, at the 3000 level.
• These are genuinely different courses. Signals and systems is about representing and transforming signals — convolution, Fourier, sampling. Feedback control is about closing a loop and making it stable — root locus, compensator design, gain and phase margin. They share the transfer function and diverge from there.
• Under SCNS the suffix is part of the course number, and equivalency does not cross it. That is what permits this situation to exist without either institution being wrong.
• What to do: identify the course by its catalog description, not by its number or by this guide's title. If your institution's EET4732 describes root locus and compensation, you are in a control systems course and this guide's emphasis is wrong for you. Get any transfer determination in writing.

⚠ Convolution and Fourier are conceptual walls — attack them with pictures

The two places where students reliably stall, and the methods that get past them.

• Convolution is a picture before it is an integral. Flip one signal, slide it across the other, and integrate the overlap at each position. Draw it. Students who compute convolution integrals symbolically without ever sketching the sliding overlap tend to get the limits wrong every time, and the limits are the entire difficulty.
• The impulse response is the system's fingerprint. Once you accept that knowing how a system answers a single impulse tells you how it answers everything, the whole subject reorganizes around one idea.
• Convolution in time is multiplication in frequency. This is the most useful single fact in the course. A hard integral becomes a product — which is precisely why engineers work in the frequency domain at all.
• Fourier is a change of basis, not a magic trick. You are rewriting a signal as a sum of sinusoids. The spectrum is a list of how much of each frequency is present. Say that to yourself until it feels obvious.
• Phase matters and is routinely ignored. Students plot magnitude spectra and forget phase carries the timing information; two signals with identical magnitude spectra can look nothing alike.
• Plot everything. With Python or MATLAB, generating a signal, transforming it, and plotting both takes minutes — and seeing a square wave's harmonics build up teaches more than a page of derivation.
• Sampling and aliasing must be understood, not memorized. The sampling theorem's consequence — that under-sampling produces a lower-frequency impostor you cannot distinguish from the real thing — is the most practically important result in the course.
• Build a transform-pair and property table as you go. Writing it is the studying.

⚠ Only about two Florida institutions carry this number — hedge accordingly

This course number appears at roughly two institutions statewide, and — as the sections above document — they do not agree on title, credit value, or scope. Content varies far more than it would for a widely taught course. Read your own institution's catalog description and syllabus rather than assuming this guide describes your section, and have any transfer evaluated in writing before you rely on it.

⚠ Engineering technology is not engineering — the articulation asymmetry

The transfer fact that costs students the most time when they learn it late.

• B.S. and B.A.S. engineering technology degrees are applied degrees, distinct from A.B.E.T.-accredited engineering programmes, and the credit does not flow freely between them.
• Engineering technology mathematics does not substitute for the engineering sequence. EGN2045 / EGN3046 ("Engineering and Technology Calculus") typically does not satisfy MAC2311 / MAC2312 for an engineering major. The asymmetry runs one way: the engineering sequence will satisfy the technology requirement, not the reverse.
• The FE exam pathway differs. Florida's PE licensure route under Chapter 471, F.S. is built around an A.B.E.T.-EAC accredited engineering degree. Graduates of engineering technology programmes face additional experience requirements, and the rules have changed over time. Rule 11 applies — verify with the Florida Board of Professional Engineers and NCEES directly, not from a programme brochure.
• This does not make the degree lesser. Engineering technology graduates are hired as engineers in fact if not in title across Florida's aerospace, defence, power, construction, and manufacturing sectors. The point is only that the two paths are not interchangeable, and switching later is expensive.
• Decide early and confirm in writing. If there is any chance you will pursue an A.B.E.T.-EAC engineering degree, take the engineering mathematics and physics sequence from the start.

How Florida course levels affect transfer

The first digit of an SCNS number denotes the year of offering, not transferability. Courses at the 1000 and 2000 levels transfer transparently between Florida public institutions, and 3000 to 4000 is unproblematic since both are upper division. The boundary that actually matters is 2000 to 3000, where lower-division credit generally cannot satisfy an upper-division requirement.

EET4732C is 4 credits and approximately 80 contact hours, matching the published 4-credit EET4158C in the same programme and prerequisite chain. Expect a mathematically demanding lecture with an integrated laboratory and computational assignments. This is typically the hardest course in an electronics engineering technology degree, and it is also the one that most changes how a graduate thinks — the systems abstraction transfers to problems that have nothing to do with electronics.