Course descriptions

Advanced programming techniques using data structures. Topics include recursion, lists, stacks, queues, trees, graphs, and hash tables.

Introductory course in digital logic and its specification and simulation. Number systems. Binary arithmetic. Boolean algebra. Combinational logic design. Sequential logic design (controllers). Data Path components (e.g., Registers, adders, register files, etc.). Memory components (e.g., RAM, ROM). Register transfer level (RTL) design.

Introduction to digital design techniques, logic gates, Medium Scale Integration (MSI) parts and flip-flops, Timing analysis, Programming and use of Programmable Logic Devices (PLD).

This course introduces discrete structures. Topics include basic logic, sets, relations, functions, proof techniques, counting methods, recursion, trees, and graphs.

Micro controller-based digital systems design methodology and techniques. Basic machine organization. Interface design. C and assembly language programming for real-time embedded systems.

Microcontroller organization and programming, Microcontroller based design, hardware and software co-design.

Analysis methods for discrete-time signals and systems in the time and frequency-domains including signal models and Fourier techniques. Continuous-time concepts are included as introductory material.

DSP programming assignments in MATLAB and/or TMS DSP processors.

Computer architecture and organization. Topics include performance evaluation, instruction, set architecture, data path, control unit, pipelining, memory hierarchy, storage, and other I/O topics.

An introduction to the principles of modern operating systems. The synchronization and communication of cooperating processes. Process Scheduling. Virtual Memory. File System design and organization. Introduction to distributed systems.

Computer Engineering Internship

Techniques for software validation and verification. Topics include: concepts of software quality (metrics, assurance, planning & implementation, process standards, validation, verification, reviews, walkthroughs and inspections). Software testing process and techniques at different levels. Validating test data.

Design of computer networks with emphasis on network architecture, protocols and standards, performance considerations, and network technologies. Topics include LAN, MAN, WAN, congestion/flow/error control, routing, addressing, broadcasting, multi-casting, switching, and inter-networking. A modeling tool is used for network design and simulation.

Computer network lab experiments with Packet Tracer, Wireshark, and other tools.

Introduction to software maintenance and re-engineering. Topics include evolution and maintenance models, re-engineering, legacy information systems, impact analysis, refactoring, program comprehension, principles of reuse and reverse engineering, approaches, and tools used to extract information from existing software systems.

Survey of artificial intelligence techniques. Topics include search, logic, knowledge representation, reasoning with uncertainty, learning, and other AI techniques.

Introduction to digital image processing. Topics include Digital image fundamentals, intensity transformations, and spatial filtering, filtering in frequency domain, Image restoration and reconstruction, Color image processing, Image compression, and Image segmentation.

Design and analysis of fault-tolerant digital systems. fault models, hardware redundancy, information redundancy, evaluation techniques, system design procedures.

Introduction to computer security and privacy. Topics include security in programs, operating systems, networks and databases.

Introduction to machine learning with images and natural text. A coverage of machine learning and data mining techniques such as decision trees, random forests, neural networks, kNN, Adaboost, stochastic gradient descent, regression, and transformers.

Robot sensors and actuators, motors, robot path planning, simultaneous localization and mapping, and robot vision.

A coverage of deep neural networks including Alexnet, convolutional neural networks, long short term memory networks, recurrent neural networks, and Resnet.

Image information, image filtering, template matching, histogram transformations, edge detection, boundary detection, region growing and pattern recognition. Complementary laboratory exercises are required.

Image and video processing lab experiments including pattern recognition, filtering, and edge detection.

Introduction to software engineering. Topics include software development life cycle, software processes, requirements engineering, software architecture and design, software testing, software evolution, and software modeling using UML

A complete design cycle. Working in small teams, students will design, document, analyze, implement, and test a product. Topics include Iteration in design, prototyping, group dynamics, design reviews, making effective presentations, concurrent design, designing for test, ethics, and standards, testing and evaluation.

A continuation of COEN 491.

Materials and device structures for applications in analog and digital electronics. Topics include characteristics and basic circuits for diode, FET transistors, BJT transistors, and operational amplifiers.

Laboratory tools and measurement techniques for basic electronic circuits using diodes, field-effect transistors, bipolar junction transistors, and operational amplifiers. Topics include DC biasing and applications in analog and digital electronics.

Circuit elements, signals, Kirchhoff’s laws, network transforms, mesh and node analysis, transient and complete response of RL, RC, and RLC circuits.

Safety, basic measurements and meters, oscilloscopes, resistor networks, measurement of capacitors and inductors, RLC circuit response.

Analysis of steady-state AC circuits, phasor notation, polyphase circuits, complex frequency, and frequency response, magnetically coupled circuits.

Magnetics and magnetically coupled circuits, electromechanical energy conversion, rotating magnetic fields, stepper motors, DC machines, induction machines, synchronous machines and brushless DC machines.

Magnetics and magnetically coupled circuits, electromechanical energy conversion, rotating magnetic fields, stepper motors, DC machines, induction machines, synchronous machines and brushless DC machines.

Power system components and transmission lines, three-phase balanced power system theory, analysis and design including economic and reliability considerations, and fault analysis.

Power system components and transmission lines, three-phase balanced power system theory, analysis and design including economic and reliability considerations, and fault analysis.

Laplace transforms, Formulation of the control problem, system equations and models, time and frequency domain analysis, stability, and design of linear control systems.

Software tools for control systems analysis.

This course provides an introduction to robotics, covering robot hardware, fundamental kinematics, trajectories, differential motion, robotic decision making, and an overview of current topics in robotics.

The lab provides students with hands-on experience in the fundamentals of robotics. The course covers essential topics like robot design, basic programming, sensors, actuators, and control systems.

Introduction to programmable automation, programmable logic controller (PLC) hardware, programming languages and techniques, closed-loop strategies using PLC’s, sensors, transducers. Case studies. Laboratory experiments.

Analysis methods for discrete-time signals and systems in the time and frequency-domains including signal models and Fourier techniques. Continuous-time concepts are included as introductory material.

Signals and systems for digital communications. Topics include signals and their spectra, source formatting, digital baseband data communication, and digital pass-band modulation and demodulation.

Laboratory and software tools for the analysis of linear and non-linear systems. Topics include spectral analysis, transforms, and applications.

Diode and transistor circuits, small signal analysis, amplifier design, differential, and operational amplifiers, flipflop circuits and wave shaping.

Experiments in design with diodes, transistors, differential and operational amplifiers, and logic components.

Static electric and magnetic fields using vector analysis and time-varying electromagnetic fields using Maxwell’s equations. Topics include Coulomb’s law, Gauss’s law, Ampere’s law, dielectric and magnetic materials, plane waves, and transmission lines.

Electrical Engineering Internship

The Renewable and Sustainable Energy Systems course offers an introductory understanding of the principles and technologies used to convert various renewable energy sources. It addresses the challenges of integrating these sources and evaluates their economic aspects for applications in heat, power, and transportation. The course also explores the future potential of each energy source and system, considering technical and sustainability challenges.

This laboratory course provides hands-on experience with current and future energy systems, energy conversion calculations and efficiency measurements. Specific labs may include photovoltaics, photocatalysis, electrocatalysis, thermochemical water-splitting, biofuel production, fuel cells, and hybrid energy systems.