LECTURE-BY-LECTURE TOPICS FOR EECS 501
| DATES | MONDAY | WEDNESDAY | FRIDAY |
| Sep. 03-07 | NO CLASS | Introduction | Prob. axioms |
| Sep. 10-14 | Countable I | Countable II | Borel Sets |
| Sep. 17-21 | Cond. Prob. | Contin. of Prob. | Random vars |
| Sep. 24-28 | Joint pdfs | Conditional pdf | 1-D derived |
| Oct. 01-05 | 2-D derived | Expectation E[.] | Variance s² |
| Oct. 08-12 | central limit | CLT examples | Inequalities |
| Oct. 15-19 | Covariance I | Covariance II | n-D Gaussian |
| Oct. 22-26 | Cond. Gauss | ML Estimation | MAP estimat |
| Oct. 29-02 | LS estimation | Estimator props | RV converg I |
| Nov. 05-09 | RV converg II | Discrete RPs I | Discrete rps II |
| Nov. 12-16 | Bernoulli RPs | Poisson RPs I | Poisson rps II |
| Nov. 19-23 | Cont-time rps | II & Markov rps | Thanksgiving |
| Nov. 26-30 | rand telegraph | Spectral density | interpret PSD |
| Dec. 03-07 | cross-spectral | smoothing filter | interpret WSS |
| Dec. 10-14 | Strong law #s | ergodic; evaluats | NO CLASS |
The following was the schedule for the Fall 2000 term.
| DATES | MONDAY | WEDNESDAY | FRIDAY |
| Sep. 04-08 | NO CLASS | Axioms of Prob. | Countable I |
| Sep. 11-15 | Countable II | Contin. of Prob. | Cond. Prob. |
| Sep. 18-22 | Combinations | Random variable | pmfs & pdfs |
| Sep. 25-29 | Joint (2D) pdfs | Conditional pdf | Derived pdfs |
| Oct. 02-06 | 2D derived pdf | Expectation E[.] | variance,covar |
| Oct. 09-13 | Pr inequalities | central limit thm | CLT examples |
| Oct. 16-20 | Covar matrix I | Covar matrix II | n-D Gaussian |
| Oct. 23-27 | Cond Gaussian | MLE estimation | MAP,LS estim |
| Oct. 30-03 | Estimator props | Convergence of.. | RV Sequences |
| Nov. 06-10 | Borel-Cantelli | Discrete-time rp | WSS thru H(z) |
| Nov. 13-17 | Bernoulli RPs | and Poisson RPs | Cont-time RPs |
| Nov. 20-24 | Cont-time II rps | and Markov RPs | Thanksgiving |
| Nov. 27-01 | Wiener,telegrph | Spectral density | Interpret,white |
| Dec. 04-08 | Wiener filtering | Spectral interpret | Strong Law #s |
| Dec. 11-15 | Periodogram bias | Course evaluation | NO CLASS |