2.161 | Fall 2008 | Graduate

Signal Processing: Continuous and Discrete

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 …
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.
Learning Resource Types
Problem Sets
Exams with Solutions
Lecture Notes
Programming Assignments
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.)