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ECE431H1 F: Digital Signal Processing (Fall 2024)

Instructor:

·      Prof. Wei Yu < weiyu@ece.utoronto.ca >

·      Office hour: By appointment

Teaching Assistants:

·      Aaron Curtis < aarond.curtis@mail.utoronto.ca > (Tutorial)

Lectures: (Starting Sept 3)

·      Tuesday 5:00 PM - 6:00 PM BA1230

·      Wednesday 3:00 PM - 5:00 PM BA1230 (No lectures on Sept 11)

Tutorials: (Starting Sept 5)

·      Thursday 11:00 AM - 12:00 PM GB248 (Sept 5 and Oct 24 tutorials are extra lectures)

Labs: (Starting Sept 12)

·      Thursday 3:00 PM - 6:00 PM SF2201 (Alternating weeks. See course schedule.)

·      Lab materials are posted on https://www.comm.utoronto.ca/~bkf/comm/ECE431/

·      Lab 1: Sampling and Quantization

·      Lab 2: Z-Transform

·      Lab 3: Fast Fourier Transform

·      Lab 4: FIR Filters

·      Lab 5: Multirate Signal Processing

Labs are done with group of 2 students. Lab report is due at the end of the lab period.

No lectures/tutorials/labs during study break: Oct 28 – Nov 1.

Last day of the session: Dec 4.

Calendar Description:

An introductory course in digital filtering and applications. Introduction to real world signal processing. Review of sampling and quantization of signals. Introduction to the discrete Fourier transform and its properties. The fast Fourier transform. Fourier analysis of signals using the discrete Fourier transform. Structures for discrete-time systems. Design and realization of digital filters: finite and infinite impulse response filters. DSP applications in areas such as communications, multimedia, video coding, human computer interaction and medicine.

Learning Objectives:

Digital signal processing (DSP) is the mathematical manipulation of an information signal to enhance or simply modify it in some way. It is characterized by the representation of discrete time, discrete frequency, or other discrete domain signals by a sequence of numbers or symbols and the processing of these signals. The objective of this course is to introduce students to fundamental concepts of DSP, including sampling and reconstruction, the z-Transform, the Discrete Fourier Transform (DFT) and its implementation, finite impulse response (FIR) and infinite impulse response (IIR) digital filtering, multirate signal processing, and applications in digital media. The course includes weekly lectures (3 hours total), weekly 1-hour tutorials, and biweekly lab sessions.

·      Understand fundamental concepts of DSP and the physical interpretation of its mathematical basis

·      Understand tradeoffs in digital representation of signals: sampling rate, quantization

·      Understand implementation of the fast Fourier transform

·      Check stability of filters

·      Analyze minimum phase, linear phase, and all-pass discrete-time systems

·      Analyze and design filters based on pole/zero placement

·      IIR filter design from continuous-time filters

·      FIR linear-phase filter design

·      Design filters using Matlab (via laboratory exercises)

·      Implementation considerations

·      Multirate processing and its application in efficient filtering, subband coding, communications, etc.

·      Application of DSP to audio, image, and video processing

Textbook:

·      V. Oppenheim and R. W. Schafer, Discrete-Time Signal Processing, 3rd Ed., Prentice Hall, 2010. ISBN-10: 0131988425, ISBN-13: 9780131988422.

Prerequisite:

·      ECE216 Signals and Systems, or ECE310 Linear Systems and Communications, or equivalent.

·      2C. Problem Analysis: Demonstrate the ability to formulate and interpret a model.

·      2D. Problem Analysis: Demonstrate the ability to execute a solution process for an engineering problem.

·      3A. Investigation: Demonstrate the ability to define a problem.

·      3B. Investigation: Demonstrate the ability to devise and execute a plan to solve a problem.

·      3C. Investigation: Demonstrate the ability to use critical analysis to reach valid conclusions supported by the results of the plan.

CEAB Accreditation Units:

·      Engineering Design (ED)         25%

·      Engineering Science (ES)         75%

Course Schedule:

 Dates Lecture Topics Textbook Labs Tutorials Sept 3-5 Introduction. Discrete-time Signals and Systems Ch. 1 Ch. 2.1-2.9 Extra Lecture Sept 5 Sept 10-12 Sampling and reconstruction of continuous-time signals. (No Lectures on Sept 11) Ch. 4.1-4.4 PRA02 Lab 1 2.29,  2.37(a)(b)  2.64, 2.67 Sept 17-19 Discrete-time processing of continuous signals Ch. 4.5 PRA01 Lab 1 4.21, 4.23,  4.31, 4.62 Sept 24-26 z-Transform Ch. 3.1-3.5 PRA02 Lab 2 3.6, 3.9, 3.40, 3.46, 3.48 Oct 1-3 Discrete Fourier Transform. Relationship between DFT, DTFT, and DTFS. Ch. 8.1-8.4 PRA01 Lab 2 Prob. Set 4 Oct 8-10 Linear and circular convolution. Windowing, spectral resolution, and spectral leakage Ch. 8.5-8.7 PRA02 Lab 3 Prob. Set 5 Oct 15-17 Fast Fourier Transform algorithm Ch. 9.1-9.4 PRA01 Lab 3 Prob. Set 6 Oct 22-24 Midterm review: Oct 22 Midterm: Oct 23, 3-5pm in-class Midterm take-up: Oct 24 Extra Lecture Oct 24 Study Break Nov 5-7 Transform analysis of linear time-invariant systems Ch. 5.1-5.6 PRA01 Lab 4 Prob. Set 7 Nov 12-14 Filter Design Ch. 7.1-7.5 PRA02 Lab 4 Prob. Set 8 Nov 19-21 Implementation of discrete-time systems Ch. 6.1-6.5 PRA01 Lab 5 Prob. Set 9 Nov 26-28 Upsampling, downsampling, and multirate systems. Quantization Ch. 4.6-4.8 PRA02 Lab 5 Prob. Set 10 Dec 3-4 Oversampling and noise shaping Final review Ch. 4.9 Final Exam

·      Labs: 20%

·      Midterm: 30%

·      Final Exam: 50%

All exams are Type C3, with Type 2 non-programmable calculator allowed, and with one double-sided 8.5in x 11in aid-sheet, supplied by the student or by the registrar’s office (handwritten or computer generated).

The final exam is scheduled by the registrar’s office in the period of December 6-23, 2024.

Course Website:

The course uses Quercus (http://q.utoronto.ca). All students must register on Quercus.  Course notices, handouts, office hours and important communications are administered using this site.

Course Policies and Information:

·      The ECE Undergraduate (UG) Office’s policy on Petition for Consider in Course Work will be employed for missed tests and late assignments. Official supporting documentation must be provided and the completed petition must be filed with the UG Office.

·      Questions regarding marking must be formally written on a piece of paper and submitted along with the associated test/assignment to the cognizant TA. There is a 72-hour limit from the time the test/assignment is first returned in which you may request a recheck.

·      Please note that late assignments (e.g., lab write-ups) will have marks deducted by 25% per business day.

·      Academic integrity is of utmost important. Any issues of plagiarism and inappropriate collaboration will be taken seriously and reported to the appropriate higher authority.

Absence Declaration:

A Verification of Illness Form (i.e., "doctor's note") is currently not required for missed academic work. Faculties or campuses may require documentation in some circumstances. Students who are absent from academic participation for any reason (e.g., COVID, cold, flu and other illness or injury, family situation) and who require consideration for missed academic work should report their absence through the online absence declaration. The declaration is available on ACORN under the Profile and Settings menu. Students should also advise their instructor of their absence. Please check with your faculty or campus for specific procedures regarding absence declarations. In some situations, documentation will be required.

Lecture Capture by Instructor:

This course, including your participation, will be recorded on video and will be available to students in the course for viewing remotely and after each session. The lecture recordings are only for the exclusive use of enrolled students, for their personal learning. Lecture recordings are not to be shared in any way beyond enrolled students. Course videos and materials belong to your instructor, the University, and/or other sources depending on the specific facts of each situation and are protected by copyright. Do not download, copy, or share any course or student materials or videos without the explicit permission of the instructor.

Syllabus Statements on Inclusivity, Accommodations & Mental Health Support

Inclusivity Statement:

All students and faculty at the University of Toronto have a right to learn, work and create in a welcoming, respectful, inclusive and safe environment.  In this class we are all responsible for our language, action and interactions. Discriminatory comments or actions of any kind will not be permitted. This includes but is not limited to acts of racism, sexism, Islamophobia, anti-Semitism, homophobia, transphobia, and ableism. As a class we will work together to create an inclusive learning environment and support each other’s learning.

If you experience or witness any form of discrimination, please reach out to the Engineering Equity Diversity & Inclusion Action Group online, an academic advisor, a U of T Equity Office, or any U of T Engineering faculty or staff member that you feel comfortable approaching.

Accommodations:

Students with diverse learning styles and needs are welcome in this course.

If you have a learning need requiring an accommodation the University of Toronto recommends that students immediately register at Accessibility Services:

·       Website: http://accessibility.utoronto.ca

·       Location: 4th floor of 455 Spadina Avenue, Suite 400

·       Phone: 416-978-8060

·       Fax: 416-978-5729

The University of Toronto supports accommodations of students with special learning needs, which may be associated with learning disabilities, mobility impairments, functional/fine motor disabilities, acquired brain injuries, blindness and low vision, chronic health conditions, addictions, deafness and hearing loss, psychiatric disabilities, communication disorders and/or temporary disabilities, such as fractures and severe sprains, recovery from an operation, serious infections or pregnancy complications.

Mental Health:

As a university student, you may experience a range of health and/or mental health issues that may result in significant barriers to achieving your personal and academic goals. The University of Toronto offers a wide range of free and confidential services and programs that may be able to assist you. We encourage you to seek out these resources early and often.

·      U of T Health & Wellness Website: https://studentlife.utoronto.ca/hwc

·      If, at some point during the year, you find yourself feeling distressed and in need of more immediate support, visit the Feeling Distressed Webpage: www.studentlife.utoronto.ca/feeling-distressed, for more campus resources.

·      Off campus, immediate help is available 24/7 through Good2Talk, a post-secondary student helpline at 1-866-925-5454.