University of Toronto
Department of Electrical & Computer Engineering
Communications Group

ECE 1511S, Fall 2023

Signal Processing

Course URL:https://q.utoronto.ca/...
Instructor: Prof. D. Hatzinakos
BAHEN BUILDING, 40 St George Str., Room 4144
Tel: 978-1613, E-mail: dimitris@comm.utoronto.ca
Overview: The course deals with some basic and some advanced topics in the area of digital signal processing. Emphasis is given to statistical signal processing with applications.
Text: No specific text will be assigned. Several sources will be recommended for reading. Class Notes for all lectures will be distributed. The notes will be available on line and can be downloaded from the course website.
Recommended text references: 1. Monson Hayes,Statistical Digital Signal Processing and Modeling, Wiley, 1996
2. Charles W. Therrien, Discrete Random Signals and Statistical Signal Processing, Prentice Hall, 1992
3. D. Manolakis, V. Ingle and S. Kogon, Statistical and adaptive signal processing, Artech House, 2005
Grading:
Weekly homework (50%) 
One to two problems or computer exercises will be assigned during each lecture. 
A report is due a week later

Project  (50%, presentation: 15%, final report: 35%)  
Student proposed individual or group projects. 
Students are expected to make a presentation on their project   during the last 
two lectures. Interactive discussion and feedback from the 
class is expected. Final project reports  are due on Dec. 20. 
Place and Time:
Tuesdays, 12:00-2:00 (Toronto time, First lecture on September 12, 2023), room BA4164
Office hours:By appointment.

Tentative Course plan

September 12, 2023 Introduction, Discrete Signal Processing and Linear Algebra fundamentals
Lecture 1(pdf),
September 19, 2023 Discrete time random processes and linear filtering
Lecture 2(pdf), Problem set 1(pdf) (Due date: September 26,2023 ), Problem set 1 solutions(pdf),
September 26, 2023 Discrete time random processes and linear filtering (continued)
Lecture 3(pdf), Problem set 2(pdf) (Due date: October 3,2023 ), Problem set 2 solutions(pdf),

October 3, 2023 Parametric modeling and statistical signal processing
Lecture 4(pdf), Problem set 3(pdf) (Due date: October 10,2023 ), ,
October 10, 2023 MSE and Wiener Filtering
Lecture 5(pdf), Problem set 4(pdf) (Due date: October 17, 2023), Term Project info(pdf) Project ref. 1, Project ref. 2, Project ref. 3
October 17, 2023 Kalman Filtering,
Lecture 6(pdf), Problem set 5(pdf) (Due date: October 24, 2023),
October 24, 2023 Adaptive systems and algorithms (LMS, RLS),
Lecture 7(pdf), Problem set 6(pdf) (Due date: Oct. 31, 2023)
October 31, 2023 Spectrum Estimation,
Deadline for project approval, Lecture 8(pdf), Problem set 7(pdf) (Due date: Nov. 14, 2023), project descriptions and group names are due.
November 14, 2023 Spectrum Estimation (continued),
Lecture 9(pdf)
November 21, 2023 Array Processing,
Lecture 10(pdf), Problem set 8(pdf) (Due date: Nov. 29, 2023
November 29, 2023 Special topics: Higher-Order Spectral Analysis (H.O.S.) ,
Lecture 11 (pdf),
December 5, 2023 Special Topics:Alpha stable processes and Fractional Lower Order moment analysis Lecture 12 (pdf),
December 12, 2023 Presentation of projects
December 19, 2023 Deadline for project reports

,

Academic Integrity policies
http://www.academicintegrity.utoronto.ca

Land Acknowledgement
I (we) wish to acknowledge this land on which the University of Toronto operates. For thousands of years it has been the traditional land of the Huron-Wendat, the Seneca, and most recently, the Mississaugas of the Credit River. Today, this meeting place is still the home to many Indigenous people from across Turtle Island and we are grateful to have the opportunity to work on this land.
Statements
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: If you have a learning need requiring an accommodation the University of Toronto recommends that students immediately register at Accessibility Services at www.studentlife.utoronto.ca/as.
Location: 4th floor of 455 Spadina Avenue, Suite 400
Voice: 416-978-8060
Fax: 416-978-5729
Email: accessibility.services@utoronto.ca

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 per sonal 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.

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.
.