Fourier Series & Wavelets

Math 414-501 — Spring 2024

Instructor: Dr. Francis J. Narcowich
Office: 611D Blocker
E-mail: f-narcowich@tamu.edu
Phone: 979-845-7554 (Messages only.)
URL: http://people.tamu.edu/~f-narcowich/
Office Hours: MW 1-2, F 12-11 and by appointment.

Catalogue Description: MATH 414. Fourier Series & Wavelets. Fourier series and wavelets with applications to data compression and signal processing. Prerequisite: MATH 304 , MATH 309 , MATH 311 , or MATH 323 ; also taught at Qatar campus.

Goals: This is a mathematics course. One of the goals is for you to learn to be able to prove theorems concerning Fourier series, properties of Fourier transforms, filters, discrete Fourier transforms (if time permits) and wavelets. Another is for you to learn these tools via examples done in class and homework problems. Finally, by means of a project, you will learn how wavelets are applied. To achieve these goals, you must diligently do the homework assignments and read the appropriate sections of the book, as well as additional notes.

Required Text: A First Course in Wavelets and Fourier Analysis, 2nd Edition, by Boggess & Narcowich. Note that, thanks to the support of Texas A&M University Libraries, you can access our text for free.

Time & Place: MWF 3-3:50 pm, BLOC 164

Programming language: Experience with MATLAB or PYTHON would be very helpful.

Grading System & Tests: Your grade will be based on a project, homework, two in-class tests (February 28, (April 10) and a final exam (May 6, 10:30-12:30). The project will count for 20% of your grade, homework for 15%, each in-class test for 20%, and the remaining 25% for the final exam. Your letter grade will be assigned this way: 90-100%, A; 80-89%, B; 70-79%, C; 60-69%, D; 59% or less, F.

Class Attendance: Attending class is very important. Roll will be taken most class days. Your class attendance will be used to decide your grade in borderline cases.

Make-up Policy: I will give make-ups (or satisfactory equivalents) only in cases authorized under TAMU Regulations. In borderline cases, I will decide whether or not the excuse is authorized. Also, if you miss a test, contact me as soon as possible.

Homework and Projects: You may consult with each other on homework problem sets, BUT only submit work which is in your own words AND be sure to cite any sources of help (either texts or people). Be aware that usually only some of the problems from an assignment will be graded. Late homework will not be accepted. Information concerning projects may be found on at this webpage: Project Information.

Academic Integrity

Copying Course Materials:   "All printed hand-outs and web-materials are protected by US Copyright Laws. No multiple copies can be made without written permission by the instructor."

Aggie Honor Code:   "An Aggie does not lie, cheat, or steal or tolerate those who do."

Authentication of work: "Texas A&M University students are responsible for authenticating all work submitted to an instructor. If asked, students must be able to produce proof that the item submitted is indeed the work of that student. Students must keep appropriate records at all times. The inability to authenticate one’s work, should the instructor request it, may be sufficient grounds to initiate an academic misconduct case (Section 20.1.2.3, Student Rule 20)." AI text generators such as ChatGPT should not be used for any work for this class without explicit permission of the instructor and appropriate attribution.

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Items that can never be identified as public information are a student’s social security number, citizenship, gender, grades, GPR or class schedule. All efforts will be made in this class to protect your privacy and to ensure confidential treatment of information associated with or generated by your participation in the class.

Directory items include name, UIN, local address, permanent address, email address, local telephone number, permanent telephone number, dates of attendance, program of study (college, major, campus), classification, previous institutions attended, degrees honors and awards received, participation in officially recognized activities and sports, medical residence location and medical residence specialization.

 

Schedule

Week Section Topic
1
Preface, 0.1-0.4 Introduction, inner product spaces
2
0.4-0.5 Inequalities, orthogonality
3
1.2.1-1.2.5 Fourier series, complex form of FS, examples
4
1.3.1-1.3.4 (simplified version) Fourier kernel, Riemann-Lebesgue lemma, proof of pointwise & uniform convergence of a Fourier series, examples
5
1.3.5, 2.1, 2.2.1 Parseval's equation, convergence in the mean, Fourier transforms, examples
6
2.2, 2.3 Properties of the FT, convolution theorem, filters
7
Test 1 (2/28), 2.4 Review, Test 1; sampling theorem
8
3.1.1-3.1.4, 3.2.1 Discrete Fourier transform, fast Fourier transform (FFT), applications, discrete signals & filters
3/11-15/24 N/A Spring Break
9
4.1, 4.2 Haar Wavelets, Haar scaling function
10
4.3, 4.4, 5.1.1; Mar. 29, Good Friday, reading day Decomposition and reconstruction algorithms, filter representation, processing a signal
11
5.1.2, 5.1.3 Multiresolution analysis (MRA), examples, scaling relation & scaling function, wavelet & wavelet spaces
12
Test 2 (4/10/24), 5.1.4 Review, Test 2; multiresolution analysis
13
5.2, 5.3.3, 6.2 Decomposition and reconstruction algorithms, connection with FT, and existence criteria for wavelets, Daubechies wavelets
14
6.2, 6.3 Classification of Daubechies' wavelets, data extensions, review;
15
6.3 Finish up. Review for final. Written form of projects due 5/1/24 at 5 pm
Monday, 5/6/24 N/A Final exam (10:30-12:30)

Updated 1/17/2024.