ELEC 301 - Signals, Systems, and Learning - Fall 2016

This course deals with signals, systems, and transforms, from their theoretical mathematical foundations to practical implementation in circuits and computer algorithms to learning algorithms that convert signals into inferences.

The first half of the course follows the classical "physics" based approach, while the second half follows the more modern "machine learning" approach. In both halves, linear algebra plays a starring role. Fundamentally important, ELEC 301 acts as a bridge between the introductory ELEC 241/2 and more advanced courses such as ELEC 302, 303, 430, 431, 437, 439, etc. in electrical and computer engineering and the broader area of data science.


Richard Baraniuk
Duncan Hall 2028, 713-348-5132, richb@rice.edu
Office hours: By appointment

Location: Duncan Hall Room 1042

Time: Tuesdays/Thursdays 1:00 to 2:15pm

Prerequisites: ELEC 241: Fundamentals of Electrical Engineering I, ELEC 242: Fundamentals of Electrical Engineering II, CAAM 335: Matrix Analysis, ELEC 303: Random Signals (co-requisite)

Additional Information:
Course Fellow
Jeff Lievense
Duncan Hall 2120, lievense@rice.edu
Office hours: TBA

Weekly Q/A Help Session
--Morganne Lerch
--Mia Polansky
--Jorge Quintero
Meeting Time: TBD

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