Applied Random Processes is an elective undergraduate class that explores stochastic systems. Stochastic systems are at the core of a number of disciplines in engineering, for example communication systems, signal processing, robotics, and machine learning. They also find application elsewhere, including social systems, markets, molecular biology and epidemiology. The course covers the theory of arrival processes (Bernoulli and Poisson) as well as Markov chains.
Learning Objectives:
The student will understand:
the classification of random processes and concepts such as strict stationarity, wide-sense stationarity and ergodicity
the concepts of correlation functions and power spectral density
Poisson, birth-death and renewal processes
Markov chains
Random walks and Brownian motion;
the concepts of filtering and prediction of a random process
Grading:
Specific details on grading can be found on the course’ s website
The courses of the Computer Science Department are designated with the letters "CS" followed by three decimal digits. The first digit denotes the year of study during which students are expected to enroll in the course; the second digit denotes the area of computer science to which the course belongs.
First Digit
Advised Year of Enrollment
1,2,3,4
First, Second, Third and Fourth year
5,6
Graduate courses
7,8,9
Specialized topics
Second Digit
Computer Science Area
0
Introductory - General
1
Background (Mathematics, Physics)
2
Hardware Systems
3
Networks and Telecommunication
4,5
Software Systems
6
Information Systems
7
Computer Vision and Robotics
8
Algorithms and Theory of Computation
9
Special Projects
The following pages contain tables (one for each course category) summarizing courses offered by the undergraduate studies program of the Computer Science Department at the University of Crete. Courses with code-names beginning with "MATH" or "PHYS" are taught by the Mathematics Department and Physics Department respectively at the University of Crete.