Signal Processing: Continuous and Discrete

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.)

Instructor(s)

MIT Course Number

2.161

As Taught In

Fall 2008

Level

Graduate

Cite This Course

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.

Rowell, Derek. 2.161 Signal Processing: Continuous and Discrete, Fall 2008. (MIT OpenCourseWare: Massachusetts Institute of Technology), http://ocw.mit.edu/courses/mechanical-engineering/2-161-signal-processing-continuous-and-discrete-fall-2008 (Accessed). License: Creative Commons BY-NC-SA


For more information about using these materials and the Creative Commons license, see our Terms of Use.


Close