ECE 331 Introduction to Random Signal Analysis and Statistics, Lec. 1, Spring 1999


See what we did in Spring 1998. Spring 99 will be quite similar.
Java Demos for Probability and Statistics (by Prof. Stanton, Cal. State Univ., San Bernardino)
Syllabus
Class Schedule for Spring 1999
1/20	Wednesday.  Overview of the course.  Covered Section 1.1, Review
	of set notation.  Started Section 2.2 on Probability Models.
	Assigned HW Ch 1: 1, 2, 3, 4, 5, 6 DUE WED. 1/27.

1/22	Finish Section 1.2.  Start Section 1.3, Axioms and Properties
	of Probability.
	

1/25 Finish Section 1.3. Section 1.4, Independence. 1/27 Section 1.5, Conditional Probability. Assigned HW Ch 1: 15, 17, 19, 20 DUE WED. 2/3. 1/29 Begin Chapter 2 on Random Variables. Section 2.1, Definition and Notation. Section 2.2, Discrete Random Variables: Bernoulli, discrete uniform, binomial.
2/1 Finish Section 2.2. Section 2.3, Multiple Random Variables. 2/3 Finished Section 2.3. Assigned HW Ch 2: 3, 4, 5, 6, 7, 9, 11 DUE WED. 2/10. 2/5 Covered Section 2.4 on Continuous Random Variables and Section 2.5 on Mixed Random Variables. Please read Examples 2.8 and 2.11
2/8 Covered Sections 2.6 and 2.7 on Cumulative Distribution Functions. 2/10 Started Chapter 4, Expectation. Assigned HW Ch 2: 13, 22, 23, 25, 26, 29, 31, 32 DUE WED. 2/17. 2/12 Finished Section 4.1 on expectation and its properties. Covered Section 4.2 on moments. Started Section 4.3 on probability generating functions.
2/15 Before class, discussed the "probability that both children are boys" problem, given that first child is a boy, or instead, given that at least one of the two children is a boy. Covered Section 4.3 on probability generating functions and Section 4.4 on moment generating functions. Almost finished Section 4.5 on characteristic functions. 2/17 Finish Section 4.5. Section 4.6 on probability bounds. Assigned HW Ch 4: 4, 8, 13, 14, 18, 19, 20, 23, 24 DUE WED. 2/24. 2/19 Worked several unassigned problems from Chapter 4. Worked Problem 17 in Chapter 2.
2/22 Begin Chapter 5, Sections 5.1 and 5.2. Handed out review questions. Extra copies are outside my office. 2/24 Continued Section 5.2 up to, but not including, the bivariate normal. 2/26 Go over review questions for exam.
3/1 Exam 1 - In class. Covers Chapters 1, 2, and 4. 3/3 Went over exam. Finished Section 5.2 on the bivariate normal density. Covered Section 5.3, Jointly Discrete RVs. Assigned HW Ch 5: 4, 5, 7, 9, 10, 13, 14 DUE WED. 3/17. 3/5 Section 5.4, Mixed RVs. Section 5.5, Expectation. Section 5.6, Independence.
3/8 NO CLASS - Spring Break 3/10 NO CLASS - Spring Break 3/12 NO CLASS - Spring Break
3/15 Started Section 5.7, Conditional Probability. 3/17 Continued with Example 5.13. Finished Section 5.7, started Section 5.8 on Conditional Expecation and the Generalized Law of Total Probability. Assigned HW Ch 5: 16, 17, 18, 20, 24, 26, 30 DUE WED. 3/24. 3/19 Finished Chapter 5. Worked parts of problem 31.
3/22 Reviewed Example 5.3. Started Chapter 6. Completed Section 6.1 and started Section 6.2. Finished Example 6.2. 3/24 Finished Section 6.2. Also included a brief discussion of the weak law of large numbers and estimating the mean of a sequence of uncorrelation RVs. Briefly discussed Chapter 7, random processes. Assigned HW Ch 5: 31(a)-(d), Ch 6: 1, 3, 5, 6 DUE WED. 3/31. 3/16 Covered Section 7.1: Mean, Correlation, and Covariance. Covered Section 7.2: Wide-Sense Stationary Processes.
3/29 Covered Section 7.3: The Power Spectral Density. Started Section 7.4: WSS Processes through LTI systems. Also noted that the characteristic function of an N(m,sigma²) is exp(j nu m - sigma²nu²/2). 3/31 Broke class into groups and had them compute E[XY], E[XZ], and E[YZ] using density from Problem 2 in Chapter 6. Continued with Section 7.4 up to Example 7.6. Assigned HW Ch 7: 3, 7, 8, 10, 11, 12 DUE WED 4/7. 4/2 Finished last two examples in Section 7.4. Covered Section 7.5: The Matched Filter.
4/5 Derived the Wiener filter of Section 7.5. 4/7 Worked problems 15 and 16 in Ch. 7. Also showed that the minimum mean squared error estimator of a random variable V based on observing another random variable U is given by the function g(u)=E[V|U=u]. In general, the function g is not linear. 4/9 Hand out exam review questions.
4/12 Review for Exam 2. 4/14 Exam 2 in class. Covers Chapters 5-7. Does not cover sections 6.3-6.5. The table of transforms on p. 77 will be given on the exam. 4/16 No class in honor of Engineering EXPO.
4/19 Went over Exam 2. 4/21 Went over handout (PoissonPr.ps) on the Poisson process. 4/23 Started Chapter 3. Assigned HW Handout on Poisson process DUE WED 4/28. Extra copies outside my office or get PDF file.
4/26 Finished Chapter 3. Started Chapter 8 on Parameter Estimation. 4/28 Continued with Chapter 8. Handed out first 3 pages of Chapter 8. 4/30 Chapter 8. Handed out complete copy of Chapter 8. Recommended problems, not collected (solutions will be posted later): Ch 3: 1, 2, 3, 4, 7(b), 8(d), 9(a) Ch 8: 1, 2, 3, 4, 6, 7, 8, 9, 10, 12; i.e., all but 5 and 11.
5/3 Covered more on Chapter 8. 5/5 Teaching Evaluations. Finish Chapter 8. Handed out old final exams.
5/11 TUESDAY, Final Exam at 12:25 pm in 2534 Engr. Hall -- Open EVERYTHING