For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| ECE4269 | Advanced Display Engineering | 3 | 6 | Major | Bachelor/Master | 1-4 | Electrical and Computer Engineering | Korean | Yes |
| This lecture deals with a various applications of display technology based on device physic and process. Thin film transistor device and process will be covered in detail to provide advanced knowledge in display technology. | |||||||||
| ECE4270 | Image Processing | 3 | 6 | Major | Bachelor/Master | 1-4 | Electrical and Computer Engineering | English | Yes |
| This class provides fundamental knowledge for acquisition, processing, display of digital image signals by studying such topics as mathematical modeling of image signal, sampling, spatial and temporal resolution, human visual system, quantization theory, basic 2D signal processing, 2D transform, frequency analysis, filtering, image enhancement, color space, color processing, and compression and reconstruction. Selected practical applications are analysed for better understanding of such techniques. | |||||||||
| ECE4272 | Advanced Convergence Capstone Design | 3 | 6 | Major | Bachelor/Master | Electrical and Computer Engineering | - | No | |
| Design addresses problems faced by local communities with a focus on design, experimentation, and prototyping processes. Particular attention is placed on constraints faced when designing for handicapped and elderly people. Multidisciplinary teams work on projects in collaboration with community partners, field practitioners, and experts in relevant fields. Topics covered include design for affordability, design for sustainability, and strategies for working effectively with community partners and customers. Students work in multidisciplinary teams on term-long projects in collaboration with community partners, field practitioners, and experts in relevant fields. Students may continue projects begun in other problem-based learning projects (such as in convergence capstone design, global convergence capstone design). | |||||||||
| ECE4273 | Introduction to Mobile Communications | 3 | 6 | Major | Bachelor/Master | Electrical and Computer Engineering | - | No | |
| This course covers various topics on mobile communications, which include cellular systems, cognitive radio networks, heterogenous wireless networks, multiple access techniques (CDMA/OFDMA/FDMA/TDMA), wireless protocol, transmission techniques in wireless channels, synchronization techniques, design and management of mobile communication networks, frequency management and next generation mobile communication systems. | |||||||||
| ECE4275 | Solid State Physics for Electrical Engineers | 3 | 6 | Major | Bachelor/Master | 1-4 | Electrical and Computer Engineering | English | Yes |
| The fundamentals of solid-state physics is to be lectured, in order to design and develop the solid-state electron devices. To figure out the basic properties of insulator/semiconductor/conductor as well as how to draw the energy band diagram, the fundamentals on solid-state physics are provided. Afterwards, students can learn how carriers are moving in semiconductor (e.g., drift, diffusion, recombination-generation). Before taking the advanced classes such as semiconductor device engineering and nano device engineering, the theory for metal-semiconductor junction and p-n junction are to be studied in great detail (including DC, AC, and transient responses). | |||||||||
| ECE4276 | Introduction to Intelligent Bioelectronic Devices | 3 | 6 | Major | Bachelor/Master | 1-4 | Electrical and Computer Engineering | - | No |
| The course covers the basic knowledge to understand interdisciplinary research area of modern flexible and stretchable devices in the field of bioelectronics. The convergence of electrical, material, and nano-scale fabricating techniques allows recent novel bioelectric platform, with a consequences in improved performance and multimodal operation. In this course work, we will discuss the electrode geometry, device structures, signal analysis, and other topics related to the implantable and biointegrated electronics. All materials in the course work requires the basic knowledge covered in other electrical engineering course from the Freshman to Junior. | |||||||||
| ECE4277 | RF System Engineering | 3 | 6 | Major | Bachelor/Master | 1-4 | Electrical and Computer Engineering | - | No |
| Modern electronic systems demand smaller, faster, and more efficient analog and digital circuits. This course introduces the fundamental concepts and analysis techniques of RF engineering to tackle the high-speed problems in designing analog and digital circuit and systems. The lecture begins with a review of the basics - the origin of resistance, capacitance, and inductance - then progresses to more advanced topics such as transmission line theory including single and multiconductor systems with eigen mode analysis, resonant circuits, impedance termination and matching, network analysis and functions and operation principles of high frequency active circuit building blocks. In addition, the course describes system level design issues with link budget analysis examples and applications in RF systems. This course will be valuable to senior undergraduate and graduate students interested in for high-speed analog and digital design. | |||||||||
| ECE4278 | SOC Design and Practice | 3 | 6 | Major | Bachelor/Master | 1-4 | Electrical and Computer Engineering | Korean | Yes |
| This course delivers fundamentals of SoC design, including basic concepts, components, and design flows. It provides an introduction to SoC and its components. It also teaches design flows of SoC, including Register-Transfer-Level (RTL) design, verification, logic synthesis, formal verification, clocking, synchronous/asynchrouns signal interface. | |||||||||
| ECE4279 | Memory Semiconductor Design | 3 | 6 | Major | Bachelor/Master | 1-4 | Electrical and Computer Engineering | English | Yes |
| CMOS memory devices are known as traditional digital devices. In order to suffice tough requirements for advanced IC’s and artificial intelligence applications, new memory devices beyond conventional DRAM/SRAM/flash are suggested. This course starts from brief review of memory system, and expands to operating principles of memory devices, design practice, and performance metrics. New memories such as emerging non-volatile memories, content addressable memory, and process-in-memory are covered at the end of course. Practice on memory circuit design and evaluation is included as a part of homework assignment. | |||||||||
| ECE4280 | Wireless Networks Cornerstone | 3 | 6 | Major | Bachelor/Master | 1-4 | Electrical and Computer Engineering | English | Yes |
| This course provides an overview on wireless networking principles and technologies from the view point of computer science majors. The major themes will focus on the fundamentals and principles covering the protocol stacks of wireless networks, and wireless data services. | |||||||||
| ECE4281 | Flexible Electronic Materials | 3 | 6 | Major | Bachelor/Master | 1-4 | Electrical and Computer Engineering | Korean | Yes |
| The course covers the basic concepts for understanding the electrical and mechanical characteristics of flexible functional electronic materials. Based the basic knowledge, we will learn fundamental technologies such as transfer-printing and printing processes for fabricating the flexible electronic devices. Based on the basic knowledge originating from Electric Circuits, Logic Circuits, and Solid State Electronic Devices, we will understand how RLC filters/amplifiers, transistors, logic gates, resistive random access memory devices stably operate under tensile/compressive strains. The aim of this class is to provide opportunities for learning the application to flexible display modules, sensors, and wireless integrated circuits. | |||||||||
| ECE4282 | AI Integrated Circuits Design | 3 | 6 | Major | Bachelor/Master | 1-4 | Electrical and Computer Engineering | Korean | Yes |
| In this course, AI Integrated Circuits are covered. Especially, recent research trends of the Processor In Memory (PIM) with the good energy efficiency will be dealt and design practice using the EDA tools will be done. | |||||||||
| ECE4283 | Intelligent System Integrated Circuit Design | 3 | 6 | Major | Bachelor/Master | 1-4 | Electrical and Computer Engineering | Korean | Yes |
| In this course, intelligent system integrated circuits are covered. Especially, recent research trends of the intelligent power management circuit, AI based sensor signal processing circuits will be dealt and design practice using the EDA tools will be done. | |||||||||
| ECE4284 | Automotive Embedded Software | 3 | 6 | Major | Bachelor/Master | Electrical and Computer Engineering | English | Yes | |
| This course describes automotive embedded software and automotive software standard architecture, AUTOSAR Classic. The aim is to understand the main characteristics of automotive embedded software and to get hands-on experience developing software based on AUTOSAR Classic. | |||||||||
| ECE4285 | Theory and coding of generative AI | 3 | 6 | Major | Bachelor/Master | Electrical and Computer Engineering | Korean | Yes | |
| Along with the rapid advancement of AI through deep learning in recent years, generative artificial intelligence (AI) models like Stable Diffusion and ChatGPT are rapidly infiltrating various industries, thus being expected to lead the Fourth Industrial Revolution. In this educational program, the goal is to understand the theory and principles behind these deep learning and generative AI models. Students will develop practical skills necessary for utilizing these powerful technologies through computer programming practical applications and projects. Specifically, this course covers: (1) Understanding and hand-on coding of deep learning models such as CNN, YOLO, Semantic Segmentation, and GANs. (2) Learning the mathematical explanation and practical applications of Diffusion models, including understanding the principles of image generation through the analysis of open-source code of Stable Diffusion. (3) Understanding language generation models like Seq2Seq and Transformer architecture used in ChatGPT, and practical applications in natural language processing and related fields. Through this course, students will gain the knowledge of current and future AI technologies and acquire the skills needed to address real-world problems. | |||||||||