This course focuses on the basic functionality of electrical and computer engineering (ECE) systems and explores the technological and scientific principles on which they are based. The goal of the course is to provide you with an introductory understanding of the operation of these systems and connections to advanced topics in ECE.
During the course, we will consider several example systems from the broad range of applications of ECE technology, including wireless communication, power, digital cameras, data storage, medical imaging, audio signal processing, GPS, feedback control, and cybersecurity. Through a combination of lectures, demonstrations, computation and simulation (using MATLAB and Excel), and hands-on labs, you will learn about the fundamentals of the design and operation of these systems. The material learned in this course will serve you as a basis for more advanced courses in the ECE curriculum.
At the end of this course, you will be able to
- Describe how electrical and computer engineering provides technological solution to address a wide range of societal challenges;
- Explain the operation of specific systems in the electrical and computer engineering domain and their basic mathematical and scientific foundations;
- Apply engineering tools and techniques to solve engineering problems;
- Perform simple lab experiments with an embedded system; and
- Identify and critique design choices in system deployed in practice.
Course Structure and Content
Lectures and Labs
This course is structured around content modules that are studied in lecture settings and hands-on experiences that are gained in a lab setting. Each content module consists of three lectures and one homework assignment. Each lab assignment consists of a 3-hour lab session.
Content Modules and Learning Outcomes
- Module 1: Digital Information and Computers
- Big-picture system: computer / embedded systems
- Module 2: Sampling and Quantization
- Big-picture system: MP3 player
- Module 3: Electromagnetic Waves
- Big-picture system: analog radio
- Module 4: Wireless Communication
- Big-picture system: cell phone
- Module 5: Power
- Big-picture system: electrical power grid
- Module 6: Optical Sensor
- Big-picture system: digital camera
- Module 7: Signals and Timing
- Big-picture system: Global Positioning System
- Module 8: Cybersecurity
- Big-picture system: Internet
- Module 9: Imaging
- Big-picture system: medical imaging
- Module 10: Analog Circuits
- Big-picture system: neuromorphic computing
- Module 11: Data Storage
- Big-picture system: memory stick / disk drive
- Module 12: Feedback Control
- Big-picture system: thermostat, …, self-balancing robot
Your final grade will be derived from your performance in three areas:
- Attendance: You are expected to attend and actively participate in lectures. Attendance is taken using a sign-in sheet.
- Homework: Homework assignments consist of sets of theoretical problems and short coding assignments. Homework will be graded using a nonlinear "A/B" grading system that encourages both thoroughness and correctness. Each homework assignment will receive two separate scores:
- A-Grade: The grade reflects the fraction of assigned problems for which complete solutions were submitted.
- B-Grade: The grade is the score achieved on a subset of the assigned problems that are selected for full grading.
- Labs: The lab grade is based on lab assignment. Note that a passing grade in the lab assignment is required to receive a passing grade in the course.
- Two Exams: There is one midterm exam during the semester and one final exam. The exams are closed-book, closed-notes and evaluate how well you retained and understood the course content as well as how well you can apply the course concepts to new problems. For each exam, an in-class review session will be held to provide time for resolving issues regarding the content and procedure of the exam.
Homework are assigned according to the schedule posted on the course website. Late submissions will not be accepted. In case of a medical emergency, late submission or a make-up exam can be requested if a note from a medical professional is provided. Midterm and final exams are held according to the schedule on the course website. The final exam is scheduled by the university.
The final grade will be norm-referenced (i.e., graded “on a curve”) with the following weighting:
- Attendance: 10%
- Homework: 15%
- Labs: 10% (passing grade required)
- Midterm 1: 20%
- Midterm 2: 20%
- Final Exam: 25%
You are encouraged to track your scores on Moodle to ensure that you have received the appropriate credit for each of your assignments and exams. No extra credit or “make-up” assignments will be given (with exception to the cases stated in the examination policy below).
The following course policies apply (in addition to all university, college, and department regulations):
- Attendance and Punctuality: You are expected to attend the all of the lectures and lab sessions for which you are enrolled. You are expected to come to lectures, labs, and examinations on time; arriving late and/or leaving early is disrespectful and disrupts the entire class.
- Late / Make-Up Policy: Assignments are due as posted. Late submissions will not be accepted except in medical emergencies or other extenuating circumstances. In such cases, late submission can be requested by contacting the instructors. Proof may be requested (e.g., note from a medical professional).
Academic Integrity: Consultation with fellow students is encouraged. However, directly copying another student's work (past or present) defeats the purpose of the assignments and is a violation of the code of conduct. Unless otherwise noted, students are expected to complete all assignment individually. Violations will result in serious penalties including course failure and possible disciplinary action. If in doubt, please consult the instructor or the official UMass guidelines regarding academic honesty (http://www.umass.edu/ombuds/honesty.php/).
Diversity and Inclusiveness
The diversity of the participants in this course is a valuable source of ideas, problem solving strategies, and engineering creativity. If you feel that your contribution is not being valued for any reason, please speak with one of the instructors privately. If you wish to communicate anonymously, you may do so in writing or speak with Dr. Paula Rees, Director of Engineering Diversity Programs (email@example.com, 413-545-6324, Marston 128). We are all members of an academic community where it is our shared responsibility to cultivate a climate where all students/individuals are valued and where both they and their ideas are treated with respect. The University and COE Diversity Mission Statement can be found here.