EE278: Introduction to Statistical Signal Processing
Overall Contents
Law of large numbers and central limit theorem; random vectors and processes; Gaussian, Markov processes; stationarity; autocorrelation and power spectral density; minimum mean square error estimation, detection, linear estimation, Kalman and Wiener filtering; Cramer Rao bound; introduction to compressed sensing.
Lectures
Announcements
11/24 to 11/28: Thanksgiving recess (no classes).
11/18: Random processes in linear systems reading posted.
11/15: Homework 7 is out. It is due Friday, 11/21.
11/08: Homework 6 is out. It is due Friday, 11/14.
11/06: Random processes reading posted.
10/31: Homework 5 is out. It is due Friday, 11/7.
10/27: Midterm Solutions are posted.
10/24: Please fill out midquarter CA evaluations.
10/24: Midterm review will be held on Oct 27 from 9 am to 11 am, in place of homework party on Tuesday.
10/21: Midterm exam will be held at Hewlett 200, on Oct 27 from 6pm to 8pm. Practice problems and solutions.
10/18: Homework 4 is out. It is due on Friday, 10/24.
10/14: No lecture today. The makeup lecture will be in Hewlett 201, from 8:10 am to 9:00 am, Friday, 10/17.
10/10: Homework 3 is out. It is due on Friday, 10/17.
10/2: Homework 2 is out. It is due on Thursday, 10/9.
9/29: Classroom changed to Hewlett 201.
9/25: Homework 1 is out. It is due on Thursday, 10/2.
