Syllabus

Instructor

Teaching Assistant

Class and Lab Meeting Time

  • Lecture: AK 231, M–R- 3 PM - 4:50PM, Oct 25 - Dec 16 (but not Nov 25)

  • Lab: AK 227, –W– 3 PM - 4:50PM, Oct 27 - Dec 15 (but not Nov 24)

Course Websites

Examination Schedule

  • Midterm Exam: Thursday, 12 November

  • Final Exam: Thursday, 16 December

Course Description

This course provides an introduction to the principles of real-time digital signal processing (DSP). The focus of this course is hands-on development of real-time signal processing algorithms using audio-based DSP kits in a laboratory environment. Basic concepts of DSP systems including sampling and quantization of continuous time signals are discussed. Trade-offs between fixed-point and floating-point processing are exposed. Real-time considerations are discussed and efiicient programming techniques leveraging the pipelined and parallel processing architecture of modern DSPs are developed. Using the audio-based DSP kits, students will implement real-time algorithms for various ltering structures and compare experimental results to theoretical predictions. Recommended background: ECE 2312, some prior experience in C programming.

Expected Outcomes

Students who successfully complete this course should be able to:

  • describe the architecture and basic operation of fixed-point and floating-point DSPs.

  • perform worst-case timing analysis and measure execution time on real-time DSP systems.

  • develop and realize computationally efficient algorithms on the DSP platform (e.g. FFT, fast convolution).

  • optimize DSP code (e.g. software pipelining).

  • draw block diagrams of FIR and IIR filters under various realization structures and describe the advantages and disadvantages of each realization structure.

  • realize real-time FIR and IIR filter designs on the DSP platform, compare experimental results to theoretical expectations, and identify the source of performance discrepancies.

Expected Background

Students taking ECE4703 should have a basic understanding of discrete time signals and systems (ECE2312 or equivalent) including a working knowledge of sampling theory, basic filter design techniques, and frequency domain analysis. Students should also have an understanding of computer architecture as well as basic C and assembly language programming skills. Finally, students in ECE4703 are expected to have some experience programming in Matlab and an understanding of basic matrix/vector operations in Matlab.

Textbook and References

  • Digital Signal Processing Using the ARM Cortex-M4, Donald S. Reay (Wiley). While the hardware required for the assignments is not identical to the hardware discussed in this book, the outline of the course will be very similar to the outline of this book.

  • Refer to the course webpage under Technical Documentation for additional reference material.

Course Work

The course includes weekly lab assignments, a midterm, and a final exam.

A small portion of your grade is for ‘class participation’. That includes any online activity that reflects your participation in the class such as asking questions and posting questions on the bulletin board.

Course Work

Grade Weight

Lab assignments (report and code)

60% of the points

Midterm

15% of the points

Final

15% of the points

Class Participation

10% of the points

Grading Policy

Final course grades are based on a student’s performance as follows:

Letter Grade

Percentage

A

90 - 100

B

80 - 90

C

70 - 80

D

60 - 70

F

< 60

Course incompletes may be granted if the major part of the course is completed; however, no additional credit can be given for missed class discussions or teamwork beyond the end of the course. In addition, in the case of an incomplete, the student is responsible for handing in the final work within the WPI required timeframe of one (1) year. After this time, an incomplete grade changes to a failing (F) grade.

Late Work Policy

Knowledge check quizzes and discussion boards will close at the deadline and no late work is accepted. Individual homework problems and team submissions will be closed at the deadline unless an extension has been discussed with the instructor in advance of the deadline and authorized by the instructor in the form of a revised deadline. In other words - if you are late, you have to talk to the instructor.

Academic Integrity

You are expected to be familiar with the Student Guide to Academic Integrity at WPI. Consequences for violating the Academic Honest Policy range from earning a zero on the assignment, failing the course, or being suspended or expelled from WPI.

Common examples of violations include:

  • Copying and pasting text directly from a source without providing appropriately cited credit

  • Paraphrasing, summarizing, or rephrasing from a source without providing appropriate citations

  • Collaborating on individual assignments

  • Turning in work where a good portion of the work is someone else’s, even if properly cited

It will be clearly stated for every assignment if group work (teaming) is allowed or not.

  • Lab assignments are governed by the Lab and Report Teaming Policy.

  • The midterm and exam are individual assignments, and no teamwork is allowed for those assignments.

Academic Accomodations

We strive to create an inclusive environment where all students are valued members of the class community. If you need course adaptations or accommodations because of a disability, or if you have medical information to share with us that may impact your performance or participation in this course, please make an appointment with us as soon as possible. If you have approved accommodations, please request your accommodation letters online through the Office of Disability Services student portal. If you have not already done so, students with disabilities who need to utilize accommodations for this course are encouraged to contact the Office of Disability Services as soon as possible to ensure that such accommodations are implemented in a timely fashion.

Tentative Schedule

Lecture/Lab

Day

Date

Topics

Lecture 0

M

10/25

Wonderful world of DSP Implementation (1)

Lab 1

W

10/27

Introduction to the Lab Kit

Lecture 1

R

10/28

Wonderful world of DSP Implementation (2)

Lecture 2

M

11/1

Sampling and Quantization, Reconstruction

Lab 2

W

11/3

FIR Filtering

Lecture 3

R

11/4

FIR Implementation Techniques

Lecture 4

M

11/8

IIR Filtering

Lab 3

W

11/10

IIR Filtering

Lecture 5

R

11/11

Real-time Input-Output

Lecture 6

M

11/15

Fixed Point DSP

Lab 4

W

11/17

Fixed Point Refinement

Lecture 7

R

11/18

DSP Libraries

Midterm

M

11/22

Lecture 8

M

11/29

Performance Analysis and Optimization

Lab 5

W

12/1

Performance Analysis and Optimization

Lecture 9

R

12/2

Digital Modulation

Lecture 10

M

12/6

Digital Demodulation

Lab 6

W

12/8

Digital Communications

Lecture 11

R

12/9

Fast Fourier Transform

T (W)

12/14

Lab Wrap-up + Kit turn-in

Final Exam

W (R)

12/15