2.161 Signal Processing: Continuous and Discrete

As taught in: Fall 2008

A blurry image of stars and its non-blurry counterpart, along with a block diagram of the system.

Data from instruments can be analyzed using filters to enhance different features; here, a deconvolution filter extracts a more detailed image from a blurry photo taken by the Hubble telescope. (Image by Prof. Derek Rowell.)

Level:

Graduate

Instructors:

Prof. Derek Rowell

Course Features

Course Description

This course provides a solid theoretical foundation for the analysis and processing of experimental data, and real-time experimental control methods. Topics covered include spectral analysis, filter design, system identification, and simulation in continuous and discrete-time domains. The emphasis is on practical problems with laboratory exercises.

Technical Requirements

Special software is required to use some of the files in this course: .m, .mat, .wav, and .zip.