Announcements
- [2009/06/29] Homework 1 has been posted and is due on July 6 before 5pm. Please see the homework section of this website to download the assignment.
- [2009/06/25] For contacting the teaching staff, please use this email address.
- [2009/06/23] Welcome to EE278! The first class is on June 24th.
Course Description
This course provides the probability and statistical signal processing background for many advanced EE courses.
Course outline:- Basic probability and random variables
Axioms, basic laws, conditional probability, Bayes rule, independence. Random variables; probability mass function, cumulative distribution function, probability density function, joint, marginal and conditional distributions. Expectation; mean, variance, covariance and correlation. Inequalities; Markov and Chebyshev. Functions of random variables. Applications: Generation of random variables. Basic detection; MAP rule, minimum probability of error. Mean square error estimation. Linear estimation.
- Random vectors
Extending cdf, pdf, and pmf to more than two random variables. Independene and conditional independence. Covariance matrix. Gaussian random vectors. Convergence and laws of large numbers. Applications: Linear estimation - the vector case.
- Random processes
Definition and examples of discrete and continuous random processes: IID, random walk, independent increment processes, Gaussian random processes. Stationarity, autocorrelation function and power spectral density. White noise, bandlimited processes. Applications: Response of linear systems to random inputs. Noise analysis in circuits. Linear estimation; infinite smoothing.
Lectures
Skilling 193, MW 3:15-5:05pm, 3 Units.
Prerequisites
Stat 116 or equivalent.
Grading
- Homework (20%)
- Midterm exam (30%)
- Final exam (50%)
Homework
- Assigned on Mondays, due the following Monday
- Approximately 5 homework sets, no homework in midterm week
Exams
- Midterm:
- July 22 (Wednesday), in-class
Teaching Staff
- Instructor E-mail contact:
- Instructors:
-
- Paul Cuff (Head instructor)
- Office: Packard 251
- Arian Maleki
- Office: Sequoia 223
- Bernd Bandemer
- Office: Packard 228
- Paul Cuff (Head instructor)
- Office Hours:
-
- Mondays 1:30-2:30pm and Wednesdays 5:15-6:15pm in Packard 109
- Administrative Associate:
- Denise Murphy
- Office: Packard 267
- Tel: 650-723-4731
- Fax: 650-724-6487
- Email: denise@ee.stanford.edu
- Denise Murphy
Reading
- Required Text
- Lecture notes "Introduction to Statistical Signal Processing", by Abbas El Gamal, available at the Stanford book store.
- Additional Reading
- These books are on hold in the Terman engineering library.
- Leon-Garcia: Probability and Random Processes for Electrical Engineers
- Gray and Davisson: Random Processes
- Papoulis: Probability, Random Variables and Stochastic Processes
- Pitman: Probability
- Ross: A First Course in Probability
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