6.342 Wavelets, Approximation, and Compression

Spring 2007 (and Spring 2009, Spring 2011, …)

 

Lectures: MW 11:00-12:30 in 1-150
Credit: 12 (3-0-9) (Grad H)

 

Instructor: Vivek Goyal, vgoyal@mit.edu

TA: Serhii Zhak, zhak@mit.edu

Prerequisites: 18.06; and 6.341 or 6.450

Overview: Hilbert space formulation of continuous-time and discrete-time signals. Sampling.  Orthogonal and biorthogonal signal expansions.  Uncertainty principles and the time-frequency plane.  Two-channel filter banks, iterated filter banks, and discrete wavelet transforms.  Multiresolution analysis.  Wavelet bases, regularity, approximation properties, and nonlinear approximation.  Basics of quantization and source coding. Compression, denoising, and other image processing using wavelets. Advanced topics from the current research literature.

More information about the course:

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