Probability and Random Processes
Fall 2020
Shyam Parekh
TuTh 1112:30 PM, Internet/Online
Office Hours: Friday 12pm
Announcements
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Lecture Schedule
Readings refer to Walrand’s “Probability in Electrical Engineering and Computer Science”. Online notes only serve as optional supplemental readings, and will not directly correspond to the lectures or textbook (see content).
Schedule is subject to some changes.
Date  Topics  Reading  Assignments 

08/27  Elementary Probability: Symmetry, Expectation, Conditioning  Appendix A.1A.5  HW 1 
09/01  Elementary Probability: Bounds, Law of Large Numbers  Appendix A.6A.9  Lab 0 
09/03  Basic Probability: Bayes Rule, Conditional RVs  Appendix B.1B.3  HW 2 
09/08  Basic Probability: Discrete RVs, Joint RVs, Independence  Appendix B.4B.5  Lab 1 
09/10  Basic Probability: Continuous RVs, Orthogonality  Appendix B.6B.7  HW 3 
09/15  PageRank: Discrete Time Markov Chains  Section 1 Markov Chains 
Lab 2 
09/17  PageRank: Reversibility, Infinite States, Classification  Section 2.12.3 Reversibility 
HW 4 
09/22  PageRank: Big Theorem  Section 2.42.5 Convergence 

09/24  No Lecture (Midterm 1)  HW 5  
09/29  Multiplexing: Gaussian RVs, CLT, Confidence Intervals  Section 3  Lab 3 
10/01  Multiplexing: Central Limit Theorem, Applications of Characteristic Functions  Section 4  HW 6 
10/06  Multiplexing/Networks: Wrapup of Multiplexing and Intro to Networks  Section 4 and Section 5.15.5 Random Graphs 
Lab 4 
10/08  Networks: Queueing, Poisson Processes  Section 5.65.10  HW 7 
10/13  Networks: Continuous Time Markov Chains  Section 6.16.2 CTMCS 
Lab 5 
10/15  Networks: CTMC Uniformization, Stationary Distribution  Section 6.36.4  HW 8 
10/20  Networks/Digital Link: Wrapup of Networks and Intro to Channel Capacity  Section 7.17.5 Information Theory 
Lab 6 
10/22  Digital Link: Hypothesis Testing, ROC Curves  Section 7.6, Section 8.18.2 Hypothesis Testing 
HW 9 
10/27  Digital Link: Statistics, Jointly Gaussian RVs  Section 8.38.4  Lab 7 
10/29  Tracking: Linear Estimation and Regression  Section 9.19.5 Hilbert Space of RVs 
HW 10 
11/03  Tracking: Minimum Mean Squared Error Estimation  Section 9.69.8  
11/05  Tracking: Introduction to Kalman Filtering  Section 10.110.2 Kalman Filter 
HW 11 
11/10  No Lecture (Midterm 2)  Lab 8  
11/12  Tracking: Kalman Filtering  Section 10.210.4  HW 12 
11/17  Route Planning: Markov Decision Problems  Section 13  Lab 9 
11/19  Route Planning: Linear Quadratic Gaussian Control  Section 14  HW 13 
11/24  Speech Recognition: Hidden Markov Models, EM Algorithm  Section 11 Hidden Markov Models 
Lab 10 
11/26  No Lecture (Thanksgiving)  
12/01  Speech Recognition: Optimization, Stochastic Gradient Descent  Section 12  HW 14 
12/03  Review 