This is an entry-level course on wireless communications, especially we will discuss how machine learning impacts the design of wireless systems. The goal is to teach fundamental and core techniques …
This course aims to provide an instruction to basic principles and tools for the analysis and design of control systems. It is intended for general graduate students in engineering and …
Provides a working knowledge of the analysis and design of linear automatic control systems using classical methods. Introduces state space techniques; dynamic models of mechanical, electrical, hydraulic and other systems; …
Studies linear dynamical systems emphasizing canonical representation and decomposition, state representation, controllability, observability, stability normal systems, state feedbacks and the decoupling problem. Representative physical examples. Cross-listed as MAE 6620. Prerequisite: …
Detailed study of graduate course material on an independent basis under the guidance of a faculty member.
Formal record of student commitment to project research under the guidance of a faculty advisor. A project report is required at the completion of each semester. May be repeated as …
A guided teaching experience for Ph.D. students, with selected teaching assignments and directed performance evaluation, under the supervision of a faculty member, as a part of Ph.D. training designed for …
A second level graduate course covering a topic not normally covered in the graduate course offerings. Topics usually reflect new developments in electrical and computer engineering and are based on …
An in-depth treatment of digital communications techniques and performance. Topics include performance of uncoded systems such as Mary, PSK, FSK, and multi-level signaling; orthogonal and bi-orthogonal codes; block and convolutional …
Formal record of student commitment to project research under the guidance of a faculty advisor. Registration may be repeated as necessary.