• Doron Levy is elected SIAM Class of 2026 Fellow

    Doron Levy was elected Fellow of the Society for Industrial and Applied Mathematics (SIAM), class of 2026:  https://www.siam.org/publications/siam-news/articles/siam-announces-2026-class-of-fellows.   Dr. Levy is recognized for his amazingly-stellar and sustained distinguished contributions to research and training in mathematical oncology and mathematical biology.  This exceedingly well-deserved award is fantastic for our department and university. Read More

  • Artem Chernikov awarded the Bessel Research Award by the Humboldt Foundation

    This award is given annually to internationally renowned academics from outside of Germany in recognition of their research accomplishments.  This award is named after Bessel and funded by the German ministry of education and research. Congratulations Atrem Chernikov.  https://www.humboldt-foundation.de/en/apply/sponsorship-programmes/friedrich-wilhelm-bessel-research-award  Read More

  • Mapping the Mind

    Junior computer science and mathematics double major Brooke Guo analyzes neural connections to understand the causes of complex brain conditions like schizophrenia.  When Brooke Guo arrived at the University of Maryland as a freshman in 2022, she knew she wanted to help people and work in a health-related field someday.… Read More

  • Four Science Terps Awarded 2025 Goldwater Scholarships

    Four undergraduates in the University of Maryland’s College of Computer, Mathematical, and Natural Sciences (CMNS) have been awarded 2025 scholarships by the Barry Goldwater Scholarship and Excellence in Education Foundation, which encourages students to pursue advanced study and research careers in the sciences, engineering and mathematics.  Over the last 16 years, UMD’s nominations… Read More

  • Announcing the Winners of the Frontiers of Science Awards

    Congratulations to our colleagues who won the 2025 Frontiers of Science Award: - Dan Cristofaro-Gardiner, for his join paper with Humbler and Seyfaddini: “Proof of the simplicity conjecture”, Annals of Mathematics 2024. - Dima Dolgopyat & Adam Kanigowski, for their joint paper with Federico Rodriguez Hertz: “Exponential mixing implies Bernoulli”, Annals of Mathematics… Read More
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Description

The goal of this course is to introduce the students to the modern mathematical techniques which are applied in signal processing and which are used in a variety of areas, ranging from engineering to medicine and finance. Topics include: Applied Linear Algebra, Frame Theory, Dimensionality Reduction and Manifold Learning, Fourier Series, Discrete Fourier Transform, Fast Fourier Transform, Wavelet Bases, Multiresolution Analysis, and Discrete Wavelet Transform, Interpolation and Sampling. Emphasis will be placed upon mathematical foundations of applicable algorithms, as well as on the ability to implement these algorithms. Will use MATLAB.

Prerequisites

Minimum grade of C- in MATH141; and 1 course with a minimum grade of C- from (MATH240, MATH461, MATH341); and familiarity with MATLAB is required.

 

Level of Rigor

Standard

 

Sample Textbooks

MATH416 Lecture Notes by Czaja and Doboszczak

 

Applications

Signal and Image Processing, Data Science, Economics, Spectroscopy

 

If you like this course, you might also consider the following courses

MATH420, MATH464, MATH475, STAT426

 

Additional Notes

An introductory course in Applied Mathematics, highly recommended for all students interested in applications and data science.

Topics

Background Material: Numbers and Computer Arithmetic, Vector Spaces and Linear Transformations; Frame Representations; Principal Component Analysis; Graphs; Laplacian Eigenmaps; Fourier Series; Discrete Fourier Transform; Fast Fourier Transform, Trigonometric Transforms; Hartley Transform; Haar Basis; Wavelet Bases; Discrete Haar Transform; Discrete Wavelet Transform; Applications to Communications, Numerical Methods, Detection, and Compression; Interpolation and Sampling.

 

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