EE 278: Introduction to
Statistical Signal Processing
Stanford University, Autumn 2009
The official EE 278 page is at
eeclass.
Teaching Staff
Instructor
- Professor Balaji Prabhakar
- Email: balaji@stanford.edu
- Office hours:
- Time: Tues 10:00am - 11:30am
- Location: Packard 269
- Phone: (650) 723-6579
Teaching Assistants
- Michelle Hewlett
- Email: ee278tas@gmail.com
- Office hours:
- Time: Tues 4:00-6:00pm
- Location: Packard 277
- Vinay Majjigi
- Email: ee278tas@gmail.com
- Office hours:
- Time: Mon 4:00-6:00pm
- Location: Packard 277
Administrative Assistant
- Denise Murphy
- Email:
denise@ee.stanford.edu
- Office hours:
- Time: MTWThF 8:30am - 4:30pm
- Location: Packard 267
- Phone: (650) 723-4731
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Course Information
- Lectures
Time: M and W 11:00am - 12:15pm
Location: Gates B03
- Problem sessions
Time: F 4:15pm - 5:05pm
Location: Gates B03
- Stanford online
Lectures and problem sessions will be available
online.
- Reading
The course reader, Introduction to Statistical Signal
Processing, by Prof. Abbas El Gamal, is available at the
Stanford Bookstore.
An additional online reference is R. Gray and L. Davisson,
Introduction to
Statistical Signal Processing.
Other references are on reserve at Terman Library.
- Prerequisites
Undergraduate courses on probability (e.g., Stat 116 / EE 178).
Linear systems and transforms (e.g., EE 102A,B / EE 261).
Warning: This is not a first course on probability. The
pace of the course in the first four weeks may be fast if you have
not already taken a first course on probability.
- Course requirements
- Weekly homework
Assigned each Wednesday and due the following
Wednesday before 5PM in the EE 278 drawer on the 2nd floor of Packard. Late homework will not be accepted. You are
allowed to work on the homework in small groups, but you must write your own
homework to hand in. You are allowed to miss one homework so we will drop your lowest
homework grade. The homeworks contain bonus questions where you can bet up to 10 points
depending on your confidence in your answer to the problem. If you are below the average on
that question, you lose the points you bet and if you are greater than the average,
you will gain some bonus points depending on how much you bet and the total point loss over the whole class.
- Midterm examination
Date and location: Monday, November
9, 11:00am - 12:45pm, TBD. Closed book/notes except
for one sheet of personal notes. - Final examination
Date and location:
Friday, December 11,
8:30am - 11:30am, TBD.
- Grading
- Homework: 15%
- Midterm examination: 25%
- Final examination: 60%
- Catalog description
Random variables, vectors, and processes;
convergence and limit theorems; IID, independent increment, Markov, and
Gaussian random processes; stationary random processes; autocorrelation and
power spectral density; mean square error estimation, detection, and linear
estimation.
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Online texts
Stanford links
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