For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| ECE5760 | Optimal Control Design | 3 | 6 | Major | Master/Doctor | 1-4 | - | 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. | |||||||||
| 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 | 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. | |||||||||
| 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 | - | 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. | |||||||||
| 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 | - | 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. | |||||||||
| 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 | - | 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. | |||||||||
| 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 | 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. | |||||||||
| 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 | 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. | |||||||||
| 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 | - | 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. | |||||||||