Laboratory experience in electrical circuit design using discrete components, standard bench equipment, and simulation in modern CAD software.

Laboratory experience in digital circuit design using modern CAD tools and programmable logic devices.

Linear circuit elements, sources, Kirchhoff’s laws, mesh and node equations, Thevenin and Norton equivalent circuits, resistive network analysis, sinusoidal steady-state analysis, power, transient analysis of simple circuits. Does not apply toward the degree requirements of Electrical and Computer Engineering majors.

Linear circuit elements, sources, Kirchhoff's laws, mesh and nodal analysis, Thevenin and Norton equivalent circuits, resistive network analysis, sinusoidal steady-state analysis, AC and DC power, transient analysis of RL, RC, and RLC circuits.

Boolean algebra, number systems and representations, analysis and design of combinational and sequential logic circuits, minimization, small- and medium-scale integrated devices, programmable logic, and simulation of digital circuits. (3-0).

This course provides the opportunity for recognition of supervised, non-research, academic experiences that are in addition to degree requirements. Registration requires approval by the department chair and sponsoring faculty member. The determination of degree credits is at the time of registration. One to three hours.

Laboratory experience in electronic design.

Analysis and design of analog and digital electronic circuits using diodes, bipolar transistors, and field effect transistors. Design and application of digital and analog circuits.

AC circuits and power, magnetically coupled circuits, analysis of networks and systems by Laplace and Fourier transform and state-variable methods, two-port networks, frequency response and network functions, transmission lines, and 3-phase ac power.

Analysis of signals and systems in the time domain using differential equations and convolution with the impulse response, and in the frequency domain using Fourier series, Fourier transforms and Laplace transforms with transfer functions.

Program development of microprocessor systems using assembly and C/C++ programming languages. Topics include processor architecture, data representation, exceptions, I/O devices, memory management, and real-time operating system principles.

Vector description of the electric and magnetic properties of free space (using the laws of Coulomb, Ampere, and Faraday). Maxwell's electromagnetic field equations. Wave propagation in unbounded regions, reflection and refraction of waves, waveguides, and transmission lines.

Introduction to the organization and design of general purpose digital computers. Topics include instruction sets, CPU structures, hardwired and microprogrammed controllers, memory, I/O systems, hardware description languages and simulations.

Computer-automated design of digital circuits. Functional specification; structural and behavioral modeling using hardware description languages; simulation for design verification and timing analysis; circuit synthesis for FPGA implementation; testing and fault diagnosis.

Advanced topics in computer architecture, including superscaler and very-long instruction word processors, parallel hardware, out-of-order processors, cache and virtual memory systems, multiprocessor systems, large data storage systems, and computer networks.

Design of avionics systems for civil and military aircraft. Topics include avionics system technology and architectures; system engineering principles; radar, electro-optical, and radio frequency sensors; displays; and communication and navigation systems.

Geometrical optics, electromagnetic waves, diffraction, interference, polarization, Fourier optics, laser fundamentals, and optical communication basics. Laboratory sessions include semiconductor laser measurement, fiber optic coupling, and Michelson interferometer setup.

This course provides an introduction to the computational methods for optics and photonics. Topics include applied numerical methods, electromagnetism, optical waveguides, and the finite-difference time-domain method. Matlab program and commercial software will be used to model different photonic devices.

This course provides an introduction to wave propagation, optical waveguide theory, and integrated photonic devices. Topics include dispersion, nonlinearity, dielectric slab waveguides, fiber optics, nanophotonic devices, and nanofabrication techniques. Students will learn fundamentals of scanning electron microscopy, atomic force microscopy, and focused ion beam technologies. It includes a hands-on simulation component using photonic design software.

Investigation of the materials used in electrical and optical devices, including metals, insulators, and semiconductors. Topics include crystal structure, quantum theory, band structure, thermal, electrical, and optical properties, and dielectric, magnetic, and superconducting properties of solids.

Topics will include an introduction to semiconductor materials (optical and electronic properties), p-n junctions, transistors, bipolar junction transistors, field effect transistors, light-emitting diodes, lasers, and photodetectors.

Introduction to the principles of operation of lasers, including interaction of light and matter, spontaneous and stimulated emission, optical gain and absorption, population inversion, optical resonators, laser rate equations, waveguides, Gaussian beams and wave propagation, and characteristics and applications of specific lasers, including gas lasers and semiconductor lasers.

Introductory course on microfabrication processes with emphasis on hands-on training in the cleanroom at the BRIC. Students will learn key microfabrication processes and get trained on cleanroom equipment used to fabricate semiconductor devices, photonic devices, microfluidic devices, and microelectromechanical systems (MEMS).

Analysis of robot manipulators, including forward and inverse kinematics, rigid-body rotation parameterizations, velocity kinematics, path planning, nonlinear dynamics, single and multi-variable control.

Introduction to electric motors and drives systems. Topics covered include dc machines, ac machines, permanent magnet machines and emerging machines topologies and their associated power electronic motor drives. Course will also cover the transformer as a static electric machine as well as linear electric machine configurations. Application specific requirements and design considerations will be covered.

Analysis and design of linear feedback control systems. Laplace transforms, transfer functions, signal-flow graphs, electrical and mechanical system modeling, state variables, system stability, time-domain response, root-locus method, Nyquist criterion, and compensator design. Laboratory exercises to illustrate course concepts.

Includes modeling, parameter identification, dynamics of high-performance induction machines, synchronous reluctance and permanent magnet machines and their control. Topics covered include, design principles, electric machine d-q modeling, dynamic simulation, control principles. The course includes computer simulations, mixed with practical hands-on laboratory experiments.

Modeling, analysis, design, and control of dynamic systems involving mechanical, electrical, thermal, and fluid components. System behavior in time and frequency domains, state-space formulation, feedback control.

Analysis of power systems, including energy sources, transmission lines, power flow, transformers, transmission and distribution systems, synchronous generators, stability, power system controls, short-circuit faults, and system protection.

Introduction to power electronic systems with emphasis on power control and switching circuits for AC/DC, DC/DC, and DC/AC converters. Associated laboratory component.

Signal analysis, modulation techniques, random signals and noise, digital transmission, information theory, coding.

Discrete-time signals and systems, sampling theory, z-transforms, spectral analysis, filter design, applications, and analysis and design of discrete signal processing systems. Credit cannot be earned for ELC 4351 if credit is earned for BME 4452.

Introduction to image formation systems that provide images for medical diagnostics, remote sensing, industrial inspection, nondestructive materials evaluation and optical copying. Image processing, including image enhancement, analysis, and compression. Student specialization through assignments and project.

See BME 4357 for course information.

Software engineering methods and tools. Topics include the development lifecycle, requirements, specifications, design, implementation, verification, validation, and maintenance, project management and professional ethics.

Characterization and design of large-scale wireless sensor networks. Topics include wireless channel utilization, media access protocols, routing, energy management, synchronization, localization, data aggregation, and security. Laboratory exercises using wireless sensor devices, cross-development, and real-time operating systems.

Covers the essentials of network architecture as well as data security and integrity. Includes relevant tools, standards, and/or engineering constraints. Local and wide area networks, wireless and mobile networks, network protocols, applications, and management. Data vulnerabilities: technical and human factors , resource protection models, secret and public key cryptography, authentication, trusted computing, and side-channel attacks.

We will explore the surprising behaviors found in the quantum world, basic principles of wave functions, and the application of quantum mechanics in systems such as quantum harmonic oscillators, semiconductors, quantum-dot cellular automata, quantum computing, and quantum communication. We also learn to use linear algebra as a description for quantum systems, since this is important in the realms of quantum computing and molecular computing.

This course introduces the student to quantum information processing. First, linear algebra is established as the mathematical language for describing quantum computing. Then, several quantum information algorithms are demonstrated, building up to Shor’s famous algorithm for defeating a widely-used classical encryption scheme. Alternate models of quantum computing, classical computing, and quantum communication also are discussed.

Principles of biomedical instrumentation and their real-world applications. Emphasis on understanding the basic design principles and technologies used in bioelectrical, biomechanical, and clinical instrumentation.

A first course in the principles of solar energy collection, conversion and storage. Topics include solar photovoltaic and thermal collectors, sun-earth geometry, ground and sky radiation models, and balance-of-system components including stratified tanks, pumps, and power inverters. Students will learn industry-standard TRNSYS energy modeling software.

Introductory course on Biosensors. Topics to be covered in this course are electrochemical sensors, immunosensors, Lab-on-a-chip biosensors, and photonic biosensors for the detection of biomolecules for the medical diagnosis.

Fundamentals of radiation and propagation, antenna parameters, linear antennas, linear and planar phased arrays, and microstrip antennas. Analysis and design principles, simulation and measurement.

Introduction to passive RF, microwave, and wireless circuit design. Topics include transmission line theory; network analysis; impedance matching techniques; design of resonators, couplers, and filters; diodes; mixers; and principles and techniques of microwave measurements.

This is a second course in radio-frequency and microwave circuits covering microwave amplifier and oscillator design. Topics include the ZY Smith chart, matching network design, gain calculations, design for amplifier stability, noise figure and low-noise amplifier design, gain matching, and negative resistance oscillator design. A final project will require the design, simulation, construction, and testing of an amplifier using microwave CAD tools and hands-on measurements.

Study of advanced topics in electrical or computer engineering. This course may be repeated once under a different topic.

Design and implementation of embedded computer systems using microcontrollers, sensors and data conversion devices, actuators, visual display devices, timers, and applications specific circuits. Software design using microprocessor cross-development systems and real-time operating system principles.

Advanced topics and/or special project activities in electrical or computer engineering.