Introduction to Applied Harmonic Analysis

Course: M 393C / CSE 396

Time/location: Tuesday & Thursday 12:30 - 2:00 (RLM 10.176) and Wednesday 5:45-7 PM (RLM 5.104)

Instructor: Rachel Ward

Office: RLM 10.144


Office Hours: Wednesday 3-5 PM, or by appointment

Target Audience: Graduate students in Math, ECE, ICES, CS, DSSC, and advanced undergraduate students

Schedule:  Please note the additional time slot on Wednesday.  This time slot will be used to make up for periods when class will not be held (see attached detailed schedule).

Class webpage:

Course Objective:  This course should serve as an introduction to mathematical building blocks from time-frequency analysis (e.g. Fourier series, wavelets, sampling theorems) that can be used for signal and image processing, numerical analysis, and statistics. The course will emphasize the connection between the analog world and the discrete world, and focus on approximation and compression of functions and data.  We will also discuss recent advances in sparse representations and compressive sensing.

Prerequisites:   Linear algebra (M341 or equivalent), probability (M 362K or equivalent), real analysis (M365C or equivalent), functional analysis or second-semester real analysis, or consent of instructor.



      The following textbooks are used as references, but are not required.

Grading Scheme: 50% Discussion/ Participation,  50% Final project

Discussion sessions:  Relevant research papers will be handed out every two weeks or so, to be presented in class by students during discussion session. Each student must present at least once, but all students are expected to have read the papers prior to presentation. Performance during these sessions will determine the discussion/participation grade.  

Tentative Schedule

Many lectures will follow the notes of Naoki Saito. Further reading on the topics of the lectures can be found here.