Master of Science in Electronics Engineering with a track in Biomedical Engineering Online

Recent and advanced topics in the design of very large- scale integrated circuits, with emphasis on mixed analog/digital circuits for telecommunications applications. Topic varies from year to year according to departmental research interests. Students may be expected to contribute lectures or seminars on selected topics.

This course will enable students to recognize, appreciate and apply mathematical and software tools to solve some of the most important problems that arise in modern engineering practice. On successful completion students will be able to apply the concept. This course covers advance mathematical tools and techniques for electronics engineering including linear algebra, advanced vector calculus, complex variable theory, ordinary and partial differential equations, and integral transform. Emphasis will be on using software such as MATLAB and Mathematical for solving engineering problems.

Topics include design and analysis of analog integrated circuits; feedback amplifier analysis and design, including stability, compensation; layout and floor planning issues associated with mixed-signal IC design; selected applications of analog circuits such as A/D and D/A converters, amplifiers, current sources; extensive use of CAD tools for design entry, simulation; and creation of an analog integrated circuit design project.

Presentation of the fundamentals of modern digital communication systems and evaluation of their performance. Topics include a brief review of random processes theory, principles of optimum receiver design for discrete and continuous messages, matched filters and correlation receivers, signal design, and error performance for various signal geometries. The course also treats aspects of system design such as propagation, link power calculations, noise models, RF components, and antennas.

A hands-on approach to microprocessor and peripheral system programming, I/O interfacing, and interrupt management. A sequence of mini-projects requiring the programming (in assembly language) of a microcontroller are conducted. A midterm and final project provide a venue for complex project design and implementation. Projects require a Motorola microcontroller evaluation board and accessories supplied by the department/student.

This course introduces both theoretical and applied techniques used to measure real world processes, design, and develop software and hardware systems to implement strategies to measure physical process using the personal computer. This course introduces the students to data acquisition and control software, personal computer hardware and Computer interfacing using a graphical programming language with instrumentation applications involving digital-to-analog conversion (DAC), analog-to-digital conversion (ADC), digital input output (DIO), Virtual Instrument System Architecture (VISA) and universal Service Bus (USB), The course focuses on projects involving computer control of instruments. The course also addresses analysis of sampled data involving use of probability density function, mean and standard derivations, correlations, and the power spectrum.

This course introduces graduate students to the concepts and theory of biomedical engineering devices, especially for sensing and modulation purposes. The course provides classroom lectures on the operation mechanism and applications of microsensors and modulators, for glucose, neurochemicals, bio-potentials, and cellular ions using electronic or optical transduction. In addition to classroom lectures, students will have a laboratory component for the design and fabrication of microscale biomedical sensors. Students will also conduct team projects to design, fabricate and analyze engineering devices and systems.

This course will enable students to recognize, appreciate and apply mathematical and software tools to solve some of the most important problems that arise in modern engineering practice. On successful completion students will be able to apply the concepts learned in EEN 610 Advanced Engineering Mathematics to control systems, digital signal processing, electromagnetics and microelectronic devices.

Provides a working knowledge of the fundamental theory, design and applications of Artificial Neural Networks (ANN). Topics include the major general architectures: backpropagation, competitive learning, counterpropagation, etc. Learning rules such as Hebbian, Widrow-Hoff, generalized delta, Kohonen linear and auto associators, etc., are presented. Specific architectures such as the Neocognitron, Hopfield-Tank, etc., are included. Hardware implementation is considered.

This project course is for non-thesis students. Students are expected to spend the semester conducting a research project. The students must work closely with their research advisor to ensure progress in the course. The course culminates with a formal written report and presentation of their research.

Basic electrical engineering principles will be applied to understand how electrical signals are generated in a biological cell and their role in proper functioning of various bioelectric systems in our body. This course covers the important concepts of bioelectrics, bioelectric system modeling and diagnosis. Although emphasis will be given to the cardiovascular system, students will be able to apply the principles of bioelectricity to any bioelectrical system.