For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| ECE5709 | Power System Computer Relaying | 3 | 6 | Major | Master/Doctor | 1-4 | Electrical and Computer Engineering | - | No |
| The field of computer relaying started with attempts to investigate whether power system functions could be performed with a digital computer. Computer relaying is beginning to contribute to all aspects of real-time monitoring and control of power systems. Relaying is thought to be the next promising and exciting field for computerization. This lesson discusses mathematical basis for protective relaying algorithms, transmission line relaying, protection of transformers, machines, & buses, hardware organization in integrated systems and system relaying & control. | |||||||||
| ECE5710 | Computer Control of Electric Power System | 3 | 6 | Major | Master/Doctor | 1-4 | Electrical and Computer Engineering | - | No |
| Increases in the size and complexity of power systems have gradually changed the requirements for control and monitoring systems. The rising cost of labor and lack of trained personnel have both contributed towards the development from a simple analog system for the remote control of a single power station to the modern computer-based energy management system for the supervision of a complete network. The objective of this lecture is to give an insight into the state-of-art of the technology of the complete power system control field. Main subjects are supervisory & control functions, man-machine communication, system structures, real-time network modeling, security management, automatic generation control and training simulators. | |||||||||
| ECE5752 | Robot Vision | 3 | 6 | Major | Master/Doctor | 1-4 | Electrical and Computer Engineering | - | No |
| Industrial robots with vision function can perform more various tasks. This course discusses low-level vision to control robots, and then techniques which implements a robot system with vision function, and finally control algorithms which are required in applying this robot system to tasks. | |||||||||
| ECE5754 | Advanced System Engineering | 3 | 6 | Major | Master/Doctor | 1-4 | Electrical and Computer Engineering | - | No |
| Advanced graduate seminar devoted to new development in theory of system and computing. Topics may include theory of public sector problems, computational algorithms, and applications of advanced mathematics to system analysis. Qualative and quantative study of the problems using techniques of system engineering and operation research, considering diverse factors such economic systems, transportation, erenry, environmental issues, etc.. | |||||||||
| ECE5756 | Real-Time System Special Topics | 3 | 6 | Major | Master/Doctor | 1-4 | Electrical and Computer Engineering | - | No |
| In this course, the issues of real-time systems are studied through the current papers. Amongst many areas of real-time systems research, a few will be selected and emphasized during the course. The research areas include languages for real-time systems, real-time system analysis, real-time OS, real-time database, real-time communication, and real-time applications. This course focuses the basic theories, design techniques, and development issues in one or two areas mentioned above. | |||||||||
| ECE5758 | Intelligent Robots | 3 | 6 | Major | Master/Doctor | 1-4 | Electrical and Computer Engineering | English | Yes |
| In order to use robots very efficiently, robots are requested to be able to perform all tasks as humans can. This course discusses the technique of sensor and its application in order to make robots perform tasks intelligently. | |||||||||
| ECE5759 | Intelligent Control | 3 | 6 | Major | Master/Doctor | 1-4 | Electrical and Computer Engineering | - | No |
| This course discusses adaptive and learning techniques in control systems. The class will discuss search techniques using the methods of gadients and stochastic approximation, Bayesian learning, linear reinforcement, and other related decision problems. | |||||||||
| ECE5760 | Optimal Control Design | 3 | 6 | Major | Master/Doctor | 1-4 | Electrical and Computer Engineering | - | No |
| Various performance indexices of control systems are introduced and the techniques to obtain the controller that minimizes a given index are explained. The class treats the topics of dynamic programming, claculus of variation, Euler-Lagrange euqtion, Hamilton-Jacobi-Bellman equation and maximum principle. | |||||||||
| ECE5761 | Estimation Theory | 3 | 6 | Major | Master/Doctor | 1-4 | Electrical and Computer Engineering | English | Yes |
| State estimation for discrete and continuous stochastic systems. Discrete and continuous Kalman filtering, optimal linear smoothing, extended Kalman filtering and adaptive Kalman filtering are presented. Real time parameter identification of stochastic systems is considered from the point of view of mean square, minimum variance, and maximum likelihood, stochastic approximation. | |||||||||
| ECE5762 | Nonlinear Systems Control Theory | 3 | 6 | Major | Master/Doctor | 1-4 | Electrical and Computer Engineering | - | No |
| Phenomena peculiar to nonlinear systems is presented. Linearization, iteration and perturbation procedures, describing function stability analysis, phase plane methods, relaxation oscillations and limit cycles is presented. Stability analysis by Lyapunov's method, Popov's theorem, adaptive control systems, sensitivity analysis is treated. | |||||||||
| ECE5902 | Writing of IT Technical Papers in English and Research Ethics | 2 | 4 | Major | Master/Doctor | 1-4 | Electrical and Computer Engineering | - | No |
| This course applies to technical papers in computer science and electrical engineering, with emphasis on papers in systems and networks. Writing the results technically is a crucial aspect of doing research. Through such communication other people can learn about and benefit from the findings. | |||||||||
| ECE5906 | Project Management | 3 | 6 | Major | Master/Doctor | 1-4 | Electrical and Computer Engineering | - | No |
| To get a high quality product of information system research and development, the management of performance, time, and resource is essential. The portion of software in this kind of project is growing, thus the traditional management which focusing on construction and/or manufacturing is not enough. By merging the components of software engineering technologies, we expect to increase the performance, to reduce the project period, and to ensure the product's quality. In this class the necessary techniques and exercise for a project manager will be provided. | |||||||||
| ECE5907 | Computer Architecture Design and Applications | 3 | 6 | Major | Master/Doctor | 1-5 | Electrical and Computer Engineering | Korean | Yes |
| The focus of the course will be on high-performance processor and memory architectures. We will explore various techniques designed to maximize parallelism and improve performance. We will look at the influence of technology on processor and memory architectures and how that may affect future processor designs. The emphasis is on the major component subsystems of high performance computers: pipelining, instruction level parallelism, memory hierarchies, input/output, and network-oriented interconnections. Students will undertake a major computing system analysis and its related project. | |||||||||
| ECE5909 | Advanced Computer Networks | 3 | 6 | Major | Master/Doctor | 1-5 | Electrical and Computer Engineering | English | Yes |
| This course is an advanced study of the computer networks in Internet. Emphasis is on understanding the network layer (3rd layer) and the transport layer (4th layer). Also optimization algorithms proposed in each layer are covered in the course. Specific topics covered include Routing, IPv6, multicasting in IP and flow, congestions controls in TCP and security issues on the computer networks. | |||||||||
| ECE5910 | Advanced Probability and Random Processes | 3 | 6 | Major | Master/Doctor | 1-5 | Electrical and Computer Engineering | - | No |
| The aim of this course is to develop a thorough understanding of the principles of random processes and knowledge of applying them to some problems in electrical engineering. First, the basic theory in probability and random process is introduced, paying particular attention to the multivariate Gaussian density function. Then, the theory of random processes and their characterization by autocorrelation and power spectral density functions is developed. The theory is then applied to the design of optimum linear systems. | |||||||||