Probability and Stochastic Processes
TeachersWATANABE, Ryuji
Grade, SemesterYear 3 2nd semest [Department of Information and Electronic Engineering, Faculty of Science and Engineering]
CategorySpecial Subjects
Elective, CreditsElective 2credit
 Syllabus Number3F323

Course Description

 This course provides an introduction to stochastic processes. The items are as follows: Basics of probability, random variable, characteristic values of the random variables, probability generating function, characteristic function, basics of stochastic processes, Poisson process, renewal process, and Markov chain. Problem solving exercises in wide areas such as social sciences, economics in addition to sciences and engineering are studied.
 The classes consist of lectures and exercises. Students will give presentations on homework assignments in the classes.
 This subject is related to the clause 3 of the diploma policy of the Department of Information and Electronic Engineering.
 

Course Objectives

 The objectives of this course for the students are to understand the basic concept of stochastic processes in probability theory and how to handle the random variables and probability distributions dependent on time and the characteristic values of the random variables.
 

Grading Policy

 The term-end examination (80%) and presentations on homework assignments in the classes (20%) will be evaluated.
 The acceptance line is accuracy rate of 60% in the above term-end examination and presentations on homework assignments.
 

Textbook and Reference

KindTitleAuthorPublisher
Textbook“Probability and Stochastic Processes” M.Fushimi Asakurashoten (2004) in Japanese. (ISBN 978-4-254-29553-5)
References“Introduction to Probability Theory” Kolmogorov A.N., Zhurbenko I.G. and Prokhorov A.V. ; translated by T.Maruyama and Y.Baba Morikita Publishing (2003) in Japanese (ISBN 4-627-09511-2)

Requirements(Assignments)

 Students are required to review the lectures and to do the homework assignments.
 

Note

 It is recommended for students to access the homework assignments on the LMS.
 It is prohibited for students to refer the textbook and notebook in term-end examination and makeup examination.
 

Schedule

1Basics of probability : Probability space, Characteristics of probability, Conditional probability, Stochastic independence
2Random variable : Random variable and distribution function, Probability function and probability density function
3Random variable : Joint distribution function, Practices
4Characteristic values of the random variables : Mean, Variance, Chebyshev’s inequality, Weak law of large numbers
5Generating function and characteristic function : Probability generating function, Characteristic function, Moment generating function
6Generating function and characteristic function : Central limit theorem, Practices
7Concept of stochastic processes : Stochastic processes, Bernoulli trial, Counting Process
8Poisson process : Poisson process, Non-homogeneous Poisson process
9Renewal process : Renewal equation, Excess life distribution
10Renewal process : Operation rate of equipment, Practices
11Markov chain : Markov chain, Transition Probability, Random walk
12Markov chain : Recursiveness, Mean first passage time
13Markov chain : Long-run distribution and stationary distribution, Brand Selection
14Markov chain : Practices
15Review, Term-end examination