Math 118 - Fourier Analysis, Wavelets and Signal Processing - Spring 2010
Lecture:
Tuesday and Thursday 12:30-2:00, 75 Evans
Course Home Page:
http://math.berkeley.edu/~strain/118.S10/index.html
Professor:
J Strain,
strain@math.berkeley.edu
Office Hours week of May 2-7:
Tuesday 1:00-2:00 pm and Wednesday 10:00-11:00 am, 1099 Evans.
Office Hours week of May 9-14:
Tuesday 1:00-2:00 pm,
Wednesday 11:00-12:00 am,
and Thursday 1:00-2:00 pm, 1099 Evans.
Description:
Introduction to signal processing including Fourier analysis and wavelets. Theory, algorithms, and applications to one-dimensional signals and multidimensional images.
Prerequisites:
Math 53 and 54 or equivalent knowledge of calculus and linear algebra.
Required Text:
Albert Boggess and Francis J. Narcowich,
A First Course in Wavelets with Fourier Analysis, second edition
(Wiley, 2009).
Other Recommended Reading:
Syllabus:
This course will cover the basic mathematical theory and
practical applications of Fourier analysis and wavelets, including
one-dimensional signal processing and multi-dimensional image
processing:
Fourier series, orthogonal systems, sampling and aliasing, FFT
Fourier integrals and transforms, linear filters, sampling theorem,
uncertainty principle, two-dimensional Fourier analysis
Haar wavelets, Daubechies wavelets, scaling functions,
multiresolution analysis, filter banks
approximation with wavelets, linear and nonlinear techniques, image
approximation and adaptive basis selection, edge detection
transform coding, signal compression, quantization, high bit-rate
compression, image and video compression
Grading:
50% for 10 best of 12 weekly problem sets, 20% midterm, 30% final
Exams:
Special accomodations: Students requiring special
accomodations for exams should contact the instructor well in advance of the
first exam so that suitable arrangements can be made.
Announcements and Handouts