82 courses with the subject ECEG, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
ECEG 500Wireless & RF Technology3
Investigation of wireless and radio frequency technology including propagation characteristics, receivers and transmitters, circuit and devices. Nonlinear and noise analysis and non-ideal components. Measurement techniques including network and spectral analysis. Communications systems are emphasized but radar and RFID systems are also covered.
A software engineering centric course covering traditional parallel computing with message passing protocols, programming patterns for multi-core processors, application development on graphics processing units, and wide scale distributed computer systems.
Response of linear spatially invariant systems; signal detection by matched filtering, mutual coherence, transform properties of linear optical imaging systems; optical information processing and filtering; linear holography.
Optical fiber structures and physical characteristics; electromagnetic waveguiding properties and modes, fiber materials, loss mechanisms, and dispersion. Semiconductor laser and LED sources and photodetectors. Connectors,Fiber measurements,communication aspects of fiber transmission. Fiber system examples and design procedures. Three credit.
Hands-on experiments and demonstrations in industrial electric drives, requirements placed by mechanical systems on electric drives, and their various applications such as flexible production systems, energy conservation, renewable energy and transportation. Power electronics in drives using switch-mode converters and pulse width modulation to synthesize the voltages in dc and ac motor drives. Design of a controller using Matlab/Simulink Cross-listed with EECE 400.
Description and analysis of continuous-time signals and systems in the time and the frequency domains' Laplace transforms:inversion of transforms by coplex integrative; application to lumped and distributed parameter systems;analysis of continuous-time linear systems using state space techniques; controllability and observability : stability analysis. Permission from Chair or Graduate Director is required.
Discrete-time signals and systems; discrete convolution; sampling and quantizing;Z-transform;discrete Fourier transform; Fast Fourier transform; state space techniques for discrete-time systems; controllability and observability; stability. Three credit Permission from Chair or Graduate Director is required.
ECEG 703Trustworthy AI Applications in Electrical & Computer Engineering3
Recently ethical, legal, and privacy consequences on humanity and environment of Artificial Intelligence (AI) has received increased attention. This course examines the trustworthiness of AI foundations related to data preparation, algorithm design, systems development, and deployment in electrical and computer engineering applications. Legal frames are investigated on how AI’s processes of development and deployment could be adapted for safety goals. As case studies, AI electrical and computer engineering applications will be examined for ethical aspects, fairness, privacy, and liability. Cross-listed with EECE 403.
Design principles of biomedical devices, bioelectronics, medical nanodevices, transducers, sensors, interface electronics, microcontrollers, and engineering programming. Signal modalities, bioelectrical signal monitoring, acquisition, analysis, and processing. Case studies and platform-based designs of medical devices, and instrumentation. Cross-listed with EECE 404.
This course will provide students with an understanding of fundamental data mining methodologies and with the ability to formulate and solve problems with them. Special emphasis attention will be paid to practical, efficient and statistically sound techniques. Hands-on experience with data mining software, primarily R, to allow development of basic execution skills. Cross-listed with EECE 478.
Radiation and simple radiating systems, wave optics, interference and diffraction: first order and higher order coherence functions; Fourier optics, properties of coherent optical beams. Three credit.
ECEG 707Electrical Power Distribution Engineering3
This course covers the fundamentals of electric power distribution systems. With increased deployment of distributed generation, controllable loads, and metering devices, it has become more and more important for researchers and power industry professionals to better understand power distribution systems. Distribution System Planning, Reliability of Electrical Distribution Systems, Quality of Electrical Power Systems, Integration of Renewable Energy into Power Systems, Energy Storage Systems, The Smart Grid, SCADA (Supervisory Control & Data Acquisition), Microgrids. Class project/research paper required. This course is cross-listed with EECE 407. Three lectures. Three credits.
Matrix calculations; linear systems and linear vector spaces; operators and their representation; function of operators and matrices; systems of differential equations; Eigen function representations; electrical engineering applications.
Random variables, distribution and density functions: functions of random variables;random processes'stationarity, ergodicity, correlation functions and power spectra' noise theory' system analysis with stochastic inputs: Gaussian, Markoff and Poisson processes. Permission from Chair or Graduate Director is required.
A study of the concept of fuzzy set theory including operations on fuzzy sets, fuzzy relations, fuzzy measures, fuzzy logic, with emphasis on engineering applications.
The proliferation of smart mobile systems gives rise to new areas of security vulnerability. This course explores the security considerations associated with smart consumer mobile devices, smartphones, mobile telecommunication systems, and sensor networks. Topics include smartphone security, mobile location privacy, and wireless sensor security. Cross-listed with EECE 417.
Topics of importance in Power Electronics including techniques for the design of Electric Vehicles, highly efficient power supplies, power factor correction and motor control systems. High voltage DC to AC power conversion methods. Vehicle battery design and charging issues. Laboratory experience with semiconductor electronic switching devices and different motor types. Cross-listed with EECE 418.
his course provides students with essential skills in performing penetration testing, vulnerability identification, and risk mitigation. Students will utilize advanced tools to detect and exploit vulnerabilities in target network environments. Cross-listed with EECE 409.
Design of embedded systems including system level modeling/specification, and architecture synthesis, compilation for area/power/performance, code compression, scheduling and real-time operating systems, and verification and functional validation of embedded systems. Case studies and platform-based design encompassing microcontrollers/digital signal processors, distributed computing and peripherals. Cross-listed with EECE 321.
Analysis and synthesis of finite state machines; Turing and universal machines; information lossless machines; modular realization of machines; introduction to machine languages and computability.
The evolution of programming from art to science. Program design tools and techniques; structured programming and modular design; complexity, storage, and processing-time analysis; program testing and debugging; software reliability, repair and availability. Three credit.
The Architecture of Digital DataTransmission Systems. The protocols:TCP/IP models.The physical layer:Wire, cable, fiber, terrestrial microwave and satellite microwave.The key concepts: bandwidth, noise, channel capacity and error detection and correction. The applications:modulation and modems. Multiplexing: FDM, slotted TDM, and statistical TDM.The data link: asynchronous and synchronous transmission, circuit switching, packet switching.
A structured coverage of Data and Computer Communications Networks. Protocols from the physical and data link layers to the applications layer. Network modeling and fundamentals of performance analysis. Time delay and reliability. Design issues, tools,and procedures regarding capacity assignments, terminal assignment, and switching node location. Routing. Examples from high speed Local Area Networks. Cross-listed with EECE 475.
A study of the modular design of operating systems; the concept of interrupts, multiple processors and I/O programming; memory management techniques, demand paging and virtual memory; job scheduling algorithms, race conditions between processes; file systems, analytic tools for the evaluation of operating systems.
ECEG 729Artificial Intelligence Applications in Electrical & Computer Engineering3
This course introduces methods for designing computer visualization, robotics, and IoT systems utilizing artificial intelligence, and machine vision. The following topics specifically related to the area of electrical and computer engineering will be covered: classification algorithms, information transference human/machines, single-agents and multi-agent Systems (MAS), expert systems, engineering knowledge presentation, automated planning, uncertain knowledge, reasoning in engineering design, simple and complex decision making, and time varying systems. Cross-listed with EECE 471.
Wireless communication systems for mobile and autonomous devices, healthcare monitoring devices, with emphasis on: cellular concept & trunking, spread spectrum systems security and multiple access techniques, speech coding, power control. Antennas and channel propagation characteristics and techniques for mitigation of propagation-related degradation factors. Analysis & design of systems following standards & protocols for the latest generation of wireless networks. Key examples of mobile portable devices, medical devices, system characteristics, and architecture design.
Performance measures: dynamic programming and its application to optimal control problems; calculus of variations; minimum principle; numerical techniques for finding optimal controls and trajectories.
ECEG 733Digital Control System Analysis and Design3
State space representation of discrete-time systems. Stability, observability, controllability. Digital controller design using transform techniques. State space design methods.
Operation of the bulk electric power system in North America. Basic types of high voltage equipment and station configurations. Methods and equipment to control power flow and voltage levels on the power systems. Cross-listed with EECE 434.
Principles of energy conversion; thermoelectric, photovoltaic, and thermionic generators; magneto hydrodynamic power generators: solar and nuclear energy conversion. Three credit.
Modern power system/energy conversion operation. Models for interconnected power grids, transmission lines, transformers, and power flow analysis. Development of basic power flow digital simulation programs and running power labs. Cross-listed with EECE 477.
North American Electric Reliability Corporation (NERC) standards and related compliance concerns in relationship to operational principles of the power systems. Cross-listed with EECE 416.
Analysis of faulted power systems, symmetrical and asymmetrical systems, transient stability, emergency control and system protection. Cross-listed with EECE 439.
Power system operation, three-phase system calculations and modeling of power system elements. Protective devices and their principles of operation. Pilot protection of transmission lines, generator protection and transformer protection.
Interaction of radiation with matter, spontaneous and simulated emission and absorption; semi-classical theory of lasers; traveling wave and cavity lasers; laser saturation; noise limitation of light detectors and amplifiers.
Detection, image formation, and engineering design of vision and imaging sensors and systems. Unmanned aerial and underwater imaging systems, biomedical image recognition, medical image understanding, inspection, and robotics applications. Cross-listed with EECE 442.
Engineering and physical principles of biomedical modalities, as applied to clinical diagnostics and pharmaceutics, gene arrays and Omics imaging technologies central to the detection process, system design, data analysis and classification. Clinical examples. Cross-listed with EECE 443.
Hypothesis testing; decision criteria: North and Wiener filtering; detection and estimation of signals with known and random parameters in white and colored Gaussian noise; recursive estimation of constant and time-varying signal parameters; Kalman-Bucy filtering; applications to communication systems, radar and biological signal processing. Prerequisite: ECEG 710.
Engineering design of miniaturized medical devices, operating on electrical, and quantum principles, with reduced form factor and weight, while reducing power consumption and boosting performance. Integration trends, functionality, scalability, reconfigurability. Case studies and platform-based designs of miniaturized medical devices, such as medical implantable devices, heart monitors, pacemakers, video cameras. Cross-listed with EECE 445.
Discrete time signals and systems analysis' infinite and finite impulse response digital filter design techniques, random discrete time signals and spectral analysis, detection and estimation of signals in noise Kalman filters.
Digital image processing for manipulation and enhancement of images, development of advanced techniques for object recognition, object classification, image reconstruction, image compression, and feature extraction. Computational analytic and interpretive approaches to optimize extraction and use of imaging data. Engineering, robotic, industrial, medical, and remote sensing applications. Cross-listed with EECE 447.
ECEG 748Applied Machine Learning for Electrical & Computer Engineering3
Fundamental concepts, methods, and technologies of machine learning. Design, modelling, implementation, and optimization of hardware architectures for machine learning systems. Machine/deep learning for signal detection, channel modeling, estimation, interference mitigation, and decoding. Performance analysis and evaluation of machine learning techniques in communication and networks systems. Machine learning for emerging communication systems and applications, such as drone systems, IoT, autonomous navigation and robotics, edge computing, smart cities, and vehicular networks. Cross-listed with EECE 448.
History of the UAV, basics of mechatronic design, common sensor payloads, high-definition cameras, sonars, lidars, vision and imaging design parameters. Major design challenges, laws and regulations, operations and safety. Cross-listed with EECE 449.
Analysis and design of various antenna types such as dipoles, horns, reflectors, apertures, microstrip and wire antennas. Electronically scanned arrays. Radiation pattern antenna impedance, gain, directivity, bandwidth, beam width, and frequency dependence. Reciprocity between receiving and transmitting antennas. Amplitude tapering to achieve desired sidelobe characteristics.
Transmission lines and waveguides; circuit representation of waveguide systems using impedance and scattering formulation , impedance transformation and matching; Faraday rotation in ferrites; passive microwave devices; terminations; attenuators; couplers, circulators, the magic tee; emphasis on developing a circuit view point for analyzing microwave devices.
Computer based technologies and informatics and computational methods that interfaces with all areas related to the discovery and development drugs, for understanding their functions, mapping processes of the cells and understanding how to use these properties to effectively develop novel drugs.
Bioinformatics principles applied to microscopic and biomedical image acquisition methods and applications, methods and applications of image analysis and related machine learning, pattern recognition and data mining techniques, image oriented multidimensional. Methods and applications for the analysis of post-translational modifications, proteomic, mass spectroscopic, and chemoinformatic data. Cross-listed with EECE 453.
Nanoparticles for optical bioimaging, optical diagnostics and light guided and activated therapy. Use of nanoparticles platforms for intracellular diagnostics and targeted drug delivery, PEBBLE nonsensors. Cross-listed with EECE 455.
Instrumentation, devices, and techniques to characterize the physiochemical, optical properties, and in vitro immunological, biological, and stability characteristics of drugs delivery, proteins, and nanomaterials. Cross-listed with EECE 456.
Animal vision combined with human vision and cognition can provide a source of inspiration for the design and development of novel computational, efficient, and robust electro-optical vision systems. The underlying philosophy of this course is to introduce new evolutionary cognitive vision systems that use artificial neurons to mimic the functions and characteristics of the human brain and drive improvements in costs, efficiency, and processing. Students taking this course will develop an integrative knowledge of bioinspired vision systems and artificial intelligence algorithms as well as the impact of biomimetic vision on a large gamma of imaging and robotic vision systems, and modalities. As a result, the students will be inspired towards the conception, and design of novel bio-inspired vision robotic applications, systems, and techniques for different segments of industry, autonomous systems, healthcare, defense, and consumer electronics. Cross-listed with EECE 457.
Cybersecurity as it relates to systems and then on the engineering principles for secure systems. The course focuses on the differences between threats and vulnerabilities, examples of cybersecurity attacks and events, frameworks, requirements and principles for securing systems. Cross-listed with EECE 458.
Methods that seeks to solve the problem of how to securely send cryptographic keys between two parties by encoding them within light particles, or photons. Quantum cryptography and key distribution technique.
Explore principles, technologies, tools, and trends in data and application security within software and hardware systems. Topics include data security fundamentals, access control models and policies, secure applications development practices, secure software and hardware architectures, trusted computing principles. Cross-listed with EECE 462.
Theoretical and practical aspects of network security. Security of TCP/IP applications; firewalls; wireless LAN security; denial-of-service defense. Cross-listed with EECE 461.
Review of probability distributions;random number testing and generation; mathematical models; Markov chains; simulation methods; data analysis; Monte Carlo methods.
Software and hardware design problems for DBMS; an overview of database systems, data manipulation languages, normal forms, machine architectures. This course will focus on basics such as the relational algebra and data model, schema normalization, query optimization, and transactions. Case studies on open-source and commercial database systems are used to illustrate these techniques and trade-offs. More topics can be added by the instructor.
Basic concepts of computer graphics systems including display devices, graphics software and the display of solid object. Point plotting procedures; line drawing algorithms and circle generators. Displays and controllers; storage and refresh devices. Two dimensional transformations; clipping and windowing. Graphics software; windowing functions, display files; geometric models. Interactive raster graphics. Three dimensional graphics including surface display, perspective and hidden surface removal. Cross-listed with EECE 436.
This course provides an overview of the latest developments and trends in wireless mobile communications, and addresses the impact of wireless transmission and user mobility on the design and management of wireless mobile systems. In addition to study the technical issues and state-of-the-art techniques in the operation and management of mobile communications networks; To learn the engineering principles and system evaluation methods used in the design of mobile communications networks. This course will cover selected Mobile Communications Networks topics in each of the following areas: Overview of wireless communications, Cellular wireless networks, 2G, 2.5G and 3G cellular networks, Long Term Evolution (LTE) - 3.5G, Future of 5G cellular networks, Wireless local area networks (Wi-Fi), Wireless personal area networks (Bluetooth, UWB, ZigBee), and Mobility management and radio resource management.
ECEG 767Big Data & Deep Learning for Electrical & Computer Engineering3
This class will focus of how to extract actionable, non-trivial knowledge from unstructured, heterogenous, massive number of data sets using machine learning and deep learning techniques. On the tool's side, we will cover the basic systems and techniques to store large volumes of data and modern systems for cluster computing based on MapReduce patterns such as Hadoop MapReduce, Apache Spark, and Flink. FPGAs, GPUs, and neuromorphic processors with emphasis on edge, fog, and cloud computing architectures, industry, manufacturing communications, autonomous navigation systems, IoT, systems, remote sensing. Cross-listed with EECE 460.
This course presents basic information on Energy outlook, interconnection issues of distributed alternate energy resources, efficiency of power production, electric energy conversion and storage (fossil fuel, nuclear, hydro, solar, fuel cells, wind, and batteries). This course also explores the different energy link integration methodologies using Matlab/Simulink. Cross-listed with EECE 466.
This course is intended to provide an introduction to remote sensing of objects with applications in defense and environment. The course covers the basic principles of image sensors and techniques, image interpretation, remote sensing theory, and digital image analysis in relation to optical, thermal and microwave remote sensing systems. Examples of remote sensing applications will be presented along with methods for obtaining quantitative information from remote sensing imagery. Students will be expected to engage in a special topic evaluation. Cross-listed with EECE 469.
This course is intended to provide the fundamental principles of space systems, in terms of electro-optical sensing, robotic vision, and imaging. Critical space missions such as monitoring of the integrity of spacecraft structures, detection of debris, object recognition and classification will be presented and discussed. Defense and commercial applications will be introduced and discussed. Cross-listed with EECE 470.
This course provides a comprehensive study of computer cloud concepts, architectures, and physical systems, technical challenges and advantages across the varied cloud service models. The course covers the essentials necessary to leverage cloud computing in a pragmatic way so that computational efficiency, cost, global scale, and productivity can be fully realized. Industrial and consumer applications and services, such as e-commerce, Industry 4, Internet of Things (IoT), video and audio streaming, will be presented.
This course provides a theoretical and practical treatment of quantum computing. Topics covered include brief quantum mechanics history, and the postulates of quantum theory. Dirac notation, quantum operators, composition, entanglement, and measurements. Quantum Computing via quantum circuit model: Description of qubit and universal set of gates. Simple quantum protocols: teleportation, superdense coding. The Deutsch-Jozsa Algorithm and the Bernstein-Vazirani Algorithm. Grover’s algorithm for searching. Entanglement and Bell’s theorem. Quantum communications and quantum error correction. Applications in cybersecurity, cryptography, financial modeling, drug development and artificial intelligence. Cross-listed with EECE 465.
This course is intended to provide the engineering and physical principles to remote sensing of objects. This course covers the principles of image sensors and techniques, image formation, interpretation and analysis, interpretation, remote sensing theory, digital image analysis. Machine learning and deep learning techniques will be applied for object recognition and classification. Defense, commercial and environmental applications will be introduced and discussed.
This course is intended to provide the engineering and physical principles for the design of space systems. Enhanced understanding of the big picture of space systems engineering processes and their application in the mission life cycle will be presented; with emphasis on the electro-optical sensing, detection, classification, monitoring of space resident objects (SRO)s. Advanced machine learning and deep learning techniques will be presented for object detection, tracking, recognition and classification. Defense, and commercial applications will be introduced and discussed.
The evolution of computer architecture spanning from the CISC machines to the RISC machines, from the pipelined to superscalar architectures; from multithreaded to parallel processors. Hardware and software processor design trade-off and performance evaluation; Data representation and instruction sets. Control design: Hardware and microprogrammed. Memory organization: Virtual segmentation and cache; system organization: Bus control and I/O. Permission from Chair or Graduate Director is required.
The objective of this course is to familiarize students with various essential aspects in harnessing wind energy and its conversion and delivery as electricity. A broad understanding of essential elements in wind-electric systems: turbines, wind- plant development and their integration into the utility grid, environmental impacts, wind forecasting and more. Cross-listed with EECE 482.
ECEG 783Cognitive-Artificial Intelligence Based Engineering Design3
Artificial intelligence is advancing rapidly, performing well-defined tasks and integrating into nearly every industry. This course explores whether artificial intelligence can achieve human-like general intelligence by exploring core principles of human behavior and cognition. Students will study key topics include vision, audition, language, learning, emotion and social cognition, creativity, and consciousness, applying their knowledge in a final group research project. Crosslisted with EECE483.
Cyber-Physical Systems (CPS) integrate physical components and computational capabilities, connected through networks, to interact and collaborate with each other and with the physical world. Security architectures for CPS, secure communication protocols, mitigation strategies, intrusion detection and prevention, and case studies on CPS security incidents. Prerequisites: EECE 210 and EECE 321. Cross-listed with EECE 488.
ECEG 790Advanced Topics in Artificial Intelligence (AI) in Electrical & Computer Engineering3
The course explores advanced Artificial Intelligence (AI) systems and tool chains on a variety of levels. The focus of the course is to utilize AI solutions to solve large-scale electrical and computer engineering problems. Topics of current interest to graduate electrical engineering and computer engineering students. The subject matter of the course will be announced in advance of the semester.
ECEG 791Advanced Topics in Power System in Electrical & Computer Engineering3
Advanced topics of current interest to graduate electrical and computer engineering students focusing on power systems. Subject matter will be announced in advance of the semester offering.
A project course of an advanced nature conducted by assigning individual investigations to be performed by the student under the supervision of a staff member; consists of theoretical and experimental investigations in specialized fields of electrical engineering of interest to the student.
ECEG 796Special Topic: in Electrical and Computer Engineering3
Topics of current interest to graduate Electrical and Computer Engineering students; subject matter will be announced in advance of semester offering. Three credits.
A Master of Science thesis option entails 24 course credits and 6 master’s research credits, namely, ECEG 799. Research undertaken under the thesis option should exhibit a thorough understanding of advanced scientific thought and an ability to apply advanced engineering design principles, and planning.
