coursemapLoading course
School of Engineering · ANU College of Systems and Society
The objective of ENGN8538 is to provide the fundamentals and advanced concepts of probability theory and random process to support graduate coursework and research in electrical, electronic and computer engineering. The required mathematical foundations will be studied at a fairly rigorous level and the applications of the probability theory and random processes to engineering problems will be emphasised. The simulation techniques will also be studied and MATLAB will be used as a software tool for bridging the probability theory and engineering applications. Topics include: • Overview of elementary probability; • Discrete and continuous random variables and their statistical properties; • Important random variables and their applications; • Functions of random variables; • Statistical properties of multiple random variables; • Random processes: Classification and characterisation; • Properties of random processes: Stationarity, correlation function, power spectral density, spectral analysis; • Special processes: such as Gaussian and Poisson; • Overview of Markov process and applications; • Estimation theory, MMSE estimation, performance comparison of estimators; • Overview of detection theory; • Simulation techniques: generation of random variable/process in MATLAB; • Examples of applications from signal processing (e.g., Wiener filter), digital communications (e.g., analysis and simulation of coded digital communication system) and mechatronic systems (e.g. estimation in simultaneous localisation and mapping).
Assignments
Learning outcomes 1, 2, 3, 4, 5, 6, 7, 8
Computer Labs
Learning outcomes 1, 2, 3, 4, 5, 6
Term Project
Learning outcomes 1, 2, 3, 4, 7, 8
Midterm Exam
Learning outcomes 1, 2, 3, 4, 5, 6
Final Exam
Learning outcomes 1, 2, 3, 4, 5, 6
Standard workload (approx. 10 hours a week). 2 lectures (1 x 2-hour lecture and 1 x 1-hour lecture) per week, up to 1 x 1-hour tutorial per week, up to 1 x 3-hour computer laboratories per week, approximately 6 hours independent study per week. Other Information Professional Skills Mapping: Mapping of Learning Outcomes to Assessment and Professional Competencies
The prescribed text for this course is: - A. Gubner, Probability and Random Processes for Electrical and Computer Engineers, Cambridge University Press, 2006. Preliminary Reading - S. L. Miller and D. Childers, Probability and Random Processes: With Applications to Signal Processing and Communications. (Online reserve: http://www.sciencedirect.com/science/book/9780121726515 ) - A. Papoulis and S.U. Pillai, Probability, Random Variables, and Stochastic Processes. - H. Stark and J. Woods, Probability, Random Processes, and Estimation Theory for Engineers. - G. R. Grimmett and D. R. Stirzaker, Probability and Random processes.