Graduate (List)

This course covers the core concept of information theory, including the fundamental source and channel coding theorems, coding theorem for Gaussian channel, rate-distortion theorem, vector quantization, multiple user channel, and multiple access channels.
(Prerequisite: CC511, EE528)

This course is meant to provide a strong foundation for graduate study and research in the area of communications. The main objective of this course is to fortify the understanding of advanced communication theories required to design and analyze digital communication systems, especially for memory channels

This course deals with the efficient coding of still image and video sequence and the international standards for transmission and storage of image information. Topics cover the representation of image signals, sampling, quantization, entropy coding, predictive coding, transform coding, subband coding, vector quantization, motion estimation, motion-compensated coding, segmentation-based coding, various international standards for bi-level image coding, still image coding and video coding.

This course aims to learn fundamental technologies for signal modeling and estimation and covers deterministic and random signal modeling, lattice filter realization, parameter, and signal estimation, Wiener and Kalman filter design, parametric and nonparametric spectrum estimation, and adaptive filtering. (Prerequisite: EE432, EE528)

The primary objective of this course is to discuss what NeuroImaging methods are available to study the brain. The focus of the course will be on modern tools capable of whole-brain imaging (mostly MRI), but we will also discuss non-MRI techniques as well. As part of the term project, students will be asked to propose novel acquisition and/or analysis method that is likely to facilitate our ability to understand the brain.

This course provides basic theory and techniques for the representation and processing of digital video. Topics include digital video formats, video spatiotemporal Sampling, 2-D/3-D motion estimation, motion segmentation, digital video filtering, video enhancement, video compression, and digital video system. In addition to the theory, students suppose to participate in experiments that are related to the above topics.

Key elements of microwave/RF ICs for wireless systems including mobile communications and radars are covered. Subcircuits including low noise amplifier, mixer, VOC, power amplifier, switches, phase shifter, and digital RF blocks are studied with their design methods, modeling methods, and characterizing methods.
(Prerequisite: EE204, EE304)

This course is designed to provide graduate students with design capability of the millimeter-wave and terahertz integrated circuits and application systems. The course starts with the active/passive device models for active and passive circuits on silicon. On-chip antenna, Beam-forming and radar blocks will be also studied for multi-Gbps wireless communication and wireless sensor applications.

The course will cover the photonic properties of nanoscale structures and devices. Basic principles and their applications are introduced.

This course involves the fundamental principles for understanding and applying fiber optic technology to modern telecommunication systems. This course starts with a brief review of a telecommunication network and covers various aspects of fiber optic communication technology including the fundamentals of fiber optic waveguides, signal degradations, photodetection, optical receiver design, fiber optic link design, and amplified WDM systems.