Graduate (List)

As the hardware complexity and power consumption of a digital system are critically affected by computer arithmetic methods, it is important in VLSI design to understand arithmetic processing methods. This class deals with diverse number systems, hardware computing structures, and detailed arithmetic methods for high-speed and low-power operations

This course deals with advanced levels of analog circuits emphasis on CMOS. The topics include wideband operational amplifiers, comparators, Switched capacitor filters, ADC, DAC, continuous time filters, etc.
(Prerequisite: EE571)

This course is designed to expose students to the important issues in high performance CMOS circuit design. This course covers the data path design in full custom design methodology, clocking strategy, and the state-of-the art CMOS logic styles.

This course is intended to present the fundamental result of analysis and design of nonlinear control systems. Especially, this course is concerned with the analysis tools for nonlinear dynamical systems and the design techniques for nonlinear control systems. (Prerequisite: EE581)

Among the various well-known intelligent control techniques, the methods of fuzzy control and neural net-based learning control are first introduced to allow for handling ambiguous/uncertain situations and effective supervised learning, respectively. Specifically, the theory of fuzzy sets and fuzzy logic-based inference mechanism are studied and the design techniques of fuzzy control are introduced. Then, the neural net learning structure is discussed and the control system based on artificial neural nets is studied. Fuzzy-neuro systems are also considered. In the second part of the course work, some other computational intelligence techniques such as GA and the rough set are briefly covered and then the basic machine learning techniques and the reinforcement learning method are studied in conjunction with their use in control system design. (Prerequisite: EE581)

This course is intended to cover kinematics, dynamics and control algorithm of a robot manipulator. After covering homogeneous transformations, kinematics equations, motion trajectory planning, we will handle various control methods. We will compare the utilization of these control methods through simulation.

This course deals with the derivation of maximum principle and the design of optimal control system. It includes an optimal design method for minimum time and energy along with dynamic programming and discrete maximum principle. Also advanced topics of optimal control are introduced. (Prerequisite: EE581)

The lecture on network management will introduce the key issues in the communications network management and will cover a new paradigm encountered in managing communications network.

This course covers mathematical theories associated with computation, convergence, communication, and synchronization of parallel and distributed algorithms which often appear in a network, communication, control, signal processing and OR problems, focusing on asynchronous parallel and distributed algorithms. A system of equations, nonlinear optimization, variational inequality problem, shortest path problem, dynamic programming, and network flow problem will be addressed as applications with many real-world examples.

The design and implementation of the physical layer, data link layer, and network layer protocols are explained. Also, client/server programming using UNIX and windows sockets is studied. Moreover, the architecture of SDR based terminal is investigated. Finally, this course involves protocol design, verification, and optimization.
(Prerequisite: EE527)