Graduate Courses Offered

Students learn classical and modern secret codes. Classical cryptography includes Viginere and substitution ciphers and cryptanalysis. Students learn number theory for RSA and AES, hashing and cryptographic protocols, block chain and digital cash, and quantum-based approaches. Additional coursework is required for those enrolled in the graduate-level course.

Credit(s): 3

Students learn the structure of electric power systems, including power system components, three-phase circuits and power flow analysis, analysis of magnetic circuits, single- and three- phase transformers, transmission line modeling, principles of energy and power conversion, and modeling and analysis of dc and ac synchronous motors and generators.

Credit(s): 3

Students study power electronics including steady-state modeling, conduction and switching losses, semiconductor power switches, converter transfer functions, topologies and dynamics, negative feedback, closed-loop transfer functions, controller stability and phase margin, regulator design, and basic magnetics theory and inductor design procedures.

Credit(s): 3

This course introduces the design and control of power converters in electric drive vehicles. It covers detailed analysis, modeling, and design of major system components. Additional coursework is required for those enrolled in the graduate-level course.

Credit(s): 3

Students receive practical, hands-on experience working with a 500W electric bike powertrain. Labs cover modeling, characterization, design, and fabrication, and culminate in e-bike system integration and demonstration. Additional coursework is required for those enrolled in the graduate-level course.

Credit(s): 0–4

This course explores generation and manipulation of light by devices. Topics include electromagnetic waves and interfaces, waveguides, basic quantum mechanics, quantum theory of light, photon angular momentum, electronic band structures, optoelectronics, photonic crystals, metamaterials, entanglement, and photonic integrated circuits.

Credit(s): 3

This course covers spacecraft communications, telemetry systems, and command and data handling. It includes an introduction to astrodynamics and orbit design, electrical power generation and storage, and spacecraft subsystems (e.g., guidance, navigation, and control).

Credit(s): 3

Students in teams perform a space system design involving all aspects, including technical, cost, and schedule. The class is linked to national design competitions and/or current USU spacecraft design projects.

Credit(s): 3

Students obtain hands-on experience in manipulating light both as classical beams and as individual quantum particles (photons), in the settings of microwave, classical optical, and quantum photonics.

Credit(s): 3

Students learn mathematical modeling of systems, including transfer function and state space representations. They study transient and steady-state responses, feedback and stability theory, and analysis and design methods of feedback controllers for single-input single output linear systems. Laboratory work required.

Credit(s): 0–4

This course covers principles of motion sensors and actuators. It also includes modeling, analysis, and identification of discrete-time dynamic systems. Digital controller design methods are taught. The course includes nonlinear effects and their compensation. Laboratory work is required.

Credit(s): 0–4

Students develop an understanding of flight control systems, including dynamic models for aircraft, low level autopilot design, state estimation, trajectory following, and path planning.

Credit(s): 3

This course presents a controls perspective to the fundamentals of mobile robotic motion control. Topics include basic kinematic motion models and primitives, graph-based obstacle-modeling and optimal graph-based planning, optimal sample-based planning, and vector field approaches.

Credit(s): 3

This course introduces students to programming in the ROS environment (an ecosystem of established and developing libraries for robotic systems) through a series of basic modules and exercises.

Credit(s): 1

Design of electronic circuits for applications in instrumentation, communication, control, and power systems.

Credit(s): 0–3

This course includes an introduction to basic algorithms and methodologies for automating the design of modern VLSI circuits. The course emphasizes physical design problems and CAD design problems using simulated annealing, dynamic programming, and mathematical programming.

Credit(s): 3

Introduces the standard cell library-based design flow in VLSI, including design methodology and IP design, CMOS circuit design styles, and design technology for low power and thermal aware designs.

Credit(s): 3

Students learn the theory and practice of testing VLSI systems. The topics cover fault modeling, fault simulation, test generation, secure hardware testing, scan design, and design for testability (DFT). Students get experience with commercial testing and DFT tools. Additional coursework is required for those enrolled in the graduate-level course.

Credit(s): 3

This course includes an introduction to computer network terminology, network applications, network technologies, and internetworking. Students are introduced to protocol stacks and each layer is studied. Particular attention is paid to the TCP/IP protocol stack.

Credit(s): 3

This course examines the structure, systems, and protocols of wireless networks, and their basic performance evaluation capabilities. The focus is on the generations of cellular networks, satellite networks, wireless LANs, WANs, and PANs. Additional coursework is required for those enrolled in the graduate-level course.

Credit(s): 3

This course covers the theory and applications of digital signal and image processing, including filter design, multi-rate processing, the FFT, and 2D systems, signals, and transforms. Some lab and computational work is required.

Credit(s): 3

Students learn real-time processor architectures and methods used for digital signal processing, including C and assembly language programming, modern DSP and GPU architectures, and finite word-length effects. The laboratory includes implementation of hardware-based real-time systems.

Credit(s): 0–4

Students explore fundamentals of analog and digital communication systems. The course focuses on modulation, demodulation, detection, and synchronization.

Credit(s): 0–3

This course covers materials, wet chemical cleaning and etch, photolithography, metal deposition, doping, carrier density and conductivity, microfluidics, and micro-electronic-mechanical-systems.

Credit(s): 3

Students are trained to use all necessary tools at the Nanoscale Device Laboratory to perform fabrication of micro/nanostructures for their research needs, including undergraduate and graduate research projects.

Credit(s): 3

Students learn advanced assembly language and systems programming concerned with performance. The course covers the study of modern computer architecture issues, such as caching, pipelining, concurrent instruction execution, and virtual memory.

Credit(s): 3

This is a course in digital design using Field-Programmable Gate Arrays (FPGAs) and it provides an introduction to VHDL. Students explore FPGAs, design tools, advanced state machines, data management, I/O interfaces, and FPGA design practices. A practical design project is included. Additional coursework is required for those enrolled in the graduate-level course.

Credit(s): 3

Modern architecture fundamentals, instruction set analysis and design, pipelined and superscalar architectures, software-hardware interaction, memory hierarchy, virtual memory stresses, and evaluation of multi-level systems.

Credit(s): 3

Students explore vulnerabilities in computer hardware, focusing on architecture's role in attacks and defenses. Topics include cache side-channel attacks, speculative execution vulnerabilities, memory-level issues like row-hammer, and fault injection attacks in artificial intelligence hardware acceleration. Additional coursework is required for those enrolled in the graduate-level course.

Credit(s): 3

Students learn real-time system design and implementation of basic concepts, including modeling, scheduling, resource access control, synchronization, and communication. Emphasis is placed on both theory and practice. Course includes exploration of open topics and current challenges in designing real-time systems and hands-on implementation.

Credit(s): 0–4

This course introduces the principled approach in cyber-physical system (CPS) design and includes its integration of computation and physical processes to network-embedded computing components. Topics include model-based design, distributed algorithms, formal specification and verification, and timed and hybrid systems.

Credit(s): 3

General plane wave solution of Maxwell's equations, potential functions, radiation, 2-D solution to Laplace's equation, and fundamental electromagnetic theory.

Credit(s): 3

Students learn microwave circuit topics such as impedance matching, microwave network analysis, waveguides, analysis and design of power dividers, and filters. Laboratory work is required.

Credit(s): 3

Theory and application of electromagnetic radiation and radiating structures. Emphasis on antenna designs for modern wireless communications and radar systems.

Credit(s): 3

Independent or group study of engineering problems not covered in regular course offerings.

Credit(s): 1–4

Introduction to stochastic processes in communications, signal processing, digital and computer systems, and control. Topics include continuous and discrete random processes, correlation and power spectral density, optimal filtering, Markov chains, and queuing theory.

Credit(s): 3

Signal representation using vector spaces. Linear algebraic techniques for signal modeling and estimation. Optimal detection and estimation algorithms, with applications.

Credit(s): 3

The theory of convex optimization and applications, as applied to engineering. Numerical methods for solving convex optimization problems are presented. Computational work required.

Credit(s): 3

Students learn classical and modern secret codes. Classical cryptography includes Viginere and substitution ciphers and cryptanalysis. Students learn number theory for RSA and AES, hashing and cryptographic protocols, block chain and digital cash, and quantum-based approaches. Additional coursework is required for those enrolled in the graduate-level course.

Credit(s): 3

Students study power electronics including steady-state modeling, conduction and switching losses, semiconductor power switches, converter transfer functions, topologies and dynamics, negative feedback, closed-loop transfer functions, controller stability and phase margin, regulator design, and basic magnetics theory and inductor design procedures.

Credit(s): 3

This course introduces the design and control of power converters in electric drive vehicles. It covers detailed analysis, modeling, and design of major system components. Additional coursework is required for those enrolled in the graduate-level course.

Credit(s): 3

Students receive practical, hands-on experience working with a 500W electric bike powertrain. Labs cover modeling, characterization, design, and fabrication, and culminate in e-bike system integration and demonstration. Additional coursework is required for those enrolled in the graduate-level course.

Credit(s): 0–4

Study of space environment and models used for engineering analysis. Topics include considerations for engineering in the space environment such as plasma interactions, debris, chemical reactions, radiation effects, and thermal issues.

Credit(s): 3

Students will submit a plan for work experience in the industry. The detailed program must have prior approval and a written report is required.

Credit(s): 1–3

Modeling, analysis, and design of multi-input, multi-output control systems, including both state space and transfer matrix approaches, with an emphasis on stability.

Credit(s): 3

This course covers spacecraft attitude dynamics and controls, including spin stabilized, three axis, dual spin modes, and attitude determination techniques.

Credit(s): 3

Applications of spacecraft attitude control concepts including attitude control and determination sensors, actuators, and algorithms.

Credit(s): 3

This course includes an introduction to basic algorithms and methodologies for automating the design of modern VLSI circuits. The course emphasizes physical design problems and CAD design problems using simulated annealing, dynamic programming, and mathematical programming. Additional coursework may be required for graduate students.

Credit(s): 3

Introduces the standard cell library-based design flow in VLSI, including design methodology and IP design, CMOS circuit design styles, and design technology for low power and thermal aware designs.

Credit(s): 3

Students learn the theory and practice of testing VLSI systems. The topics cover fault modeling, fault simulation, test generation, secure hardware testing, scan design, and design for testability (DFT). Students get experience with commercial testing and DFT tools. Additional coursework is required for those enrolled in the graduate-level course.

Credit(s): 3

Fundamentals of aircraft and spacecraft navigation systems. Techniques in celestial and inertial navigation. Global Positioning System (GPS) principles. Least squares estimation and Kalman filtering for optimal estimation of stochastic systems.

Credit(s): 3

This course covers N-dimensional constrained and unconstrained nonlinear parameter and dynamic system optimization. It emphasizes solutions to optimal spacecraft trajectory problems and optimal guidance algorithms. It also covers the Space Shuttle Powered-Explicit-Guidance (PEG).

Credit(s): 3

This course examines the structure, systems, and protocols of wireless networks, and their basic performance evaluation capabilities. The focus is on the generations of cellular networks, satellite networks, wireless LANs, WANs, and PANs. Additional coursework is required for those enrolled in the graduate-level course.

Credit(s): 3

Students learn the mathematics of wave motion, electromagnetic theory of light, light propagation, geometrical optics, and superposition of waves. Additional coursework is required for those enrolled in the graduate-level course.

Credit(s): 3

This is a course in digital design using Field-Programmable Gate Arrays (FPGAs) and it provides an introduction to VHDL. Students explore FPGAs, design tools, advanced state machines, data management, I/O interfaces, and FPGA design practices. A practical design project is included. Additional coursework is required for those enrolled in the graduate-level course.

Credit(s): 3

This is an advanced course in digital design and processing using Field-Programmable Gate Arrays (FPGAs). Students explore software/hardware co-design, reconfigurable processors, I/O interfaces, pipelining, parallelism, and modern FPGA design practices. The course is lab-intensive and includes a practical design project.

Credit(s): 3

Modern architecture fundamentals, instruction set analysis and design, pipelined and superscalar architectures, software-hardware interaction, memory hierarchy, virtual memory stresses, and evaluation of multi-level systems.

Credit(s): 3

Students explore vulnerabilities in computer hardware, focusing on architecture's role in attacks and defenses. Topics include cache side-channel attacks, speculative execution vulnerabilities, memory-level issues like row-hammer, and fault injection attacks in artificial intelligence hardware acceleration. Additional coursework is required for those enrolled in the graduate-level course.

Credit(s): 3

Students learn real-time system design and implementation of basic concepts, including modeling, scheduling, resource access control, synchronization, and communication. Emphasis is placed on both theory and practice. The course includes exploration of open topics and current challenges in designing real-time systems and hands-on implementation.

Credit(s): 0–4

This course introduces the principled approach in cyber-physical system (CPS) design and includes its integration of computation and physical processes to network-embedded computing components. Topics include model-based design, distributed algorithms, formal specification and verification, and timed and hybrid systems.

Credit(s): 3

Weekly seminars or colloquia. Students are normally required to enroll for two semesters.

Credit(s): 0.5

Students learn about microwave amplifier design for noise, gain, and power match; microwave semiconductor and vacuum-tube devices; microwave oscillators; and microwave system performance characterization. Laboratory work is required.

Credit(s): 3

Independent or group study in electrical engineering topics, such as automated systems, optics and laser engineering, electro-acoustics, solid-state materials, devices, and intelligent systems engineering.

Credit(s): 1–6

Design Project

Credit(s): 3

This course is designed for students preparing a master’s degree thesis.

Credit(s): 1–6

This course provides graduate students with continued support and advisement. It is usually taken following completion of all coursework required for the degree.

Credit(s): 1–6

Foundations of detection theory, including Neyman-Pearson, Bayes, and Minimax Bayes detection. Maximum likelihood and Bayes estimation theory. Recursive estimation and Kalman filtering and smoothing. Expectation maximization and hidden Markov models.

Credit(s): 3

This course introduces advanced modeling and control topics in power electronics, including design-oriented analysis, averaged switch modeling, AC modeling of the discontinuous conduction mode, the current programmed mode, input filter design, digital control of switched-mode power converters, and low-harmonic rectifiers.

Credit(s): 3

This course presents analysis methods and design challenges associated with soft-switching and resonant converters. It introduces mechanisms of switching loss and soft switching techniques, steady-state analysis in the time and frequency domains, and analysis of various resonant and soft-switching DC-DC and DC-AC converters.

Credit(s): 3

Theory, engineering, and data reduction techniques of spacecraft instrumentation for space science and spacecraft systems.

Credit(s): 3

Methods of nonlinear and adaptive control system design and analysis. Includes qualitative and quantitative theories, graphical methods, frequency domain methods, sliding surface design, linear parameter estimation methods, and direct and indirect adaptive control techniques.

Credit(s): 3

The application of multi-variable optimal control techniques to aircraft, missiles and spacecraft.

Credit(s): 3

Students learn advanced methods of control system analysis and design. These include operator approaches to optimal control, such as LQR, LQG, and L1 optimization techniques.

Credit(s): 3

This course covers probability theory, stochastic system models, optimal estimation for linear systems, optimal smoothing, and optimal estimation for nonlinear systems. Applications of these concepts include orbit determination, real-time position, velocity, and attitude determination for rockets, aircraft, and spacecraft.

Credit(s): 3

This course covers the theory and applications of Monte Carlo and Linear Covariance techniques to closed-loop aerospace systems.

Credit(s): 3

Students learn advanced digital signal and image processing theory and methods. Topics are selected from optimal filter design, adaptive filtering, spectral estimation, beamforming, tomography, data compression, restoration/superresolution, machine vision, etc.

Credit(s): 3

Course Description:Students examine codes employed in digital communications, including a discussion of error correction codes over finite fields. Students learn Reed-Solomon, convolutional, and trellis coding. Advanced coding techniques are also presented.

Credit(s): 3

Covers parallelism and the design of parallel computer architectures. Explores various hardware techniques designed to support parallel execution across a range of real-world applications. Examines various components of parallel computer systems and design trade-offs in the light of underlying circuit characteristics.

Credit(s): 3

Students learn analysis and synthesis of distributed controllers for multi-agent systems with different levels of complexity and objectives. Topics include graph theory, output regulation, and synchronization problems spanning consensus/formation of single integrators to cooperative output regulation of uncertain dynamics.

Credit(s): 3

In this course, students learn the Finite Difference Time Domain (FDTD) and Finite Element Method (FEM) approaches for solving electromagnetics problems, including waveguides, scattering problems, and electromagnetic wave propagation in different media.

Credit(s): 3

Modeling electromagnetic problems with integral equations and solve using Methods of Moments (MOM). Solving complex electromagnetic problems using Boundary Integral Finite Element Method (BI-FEM), which is a hybrid computational electromagnetic method by integration MOM and Finite Element Method (FEM).

Credit(s): 3

Independent or group study in electrical engineering topics, such as automated systems, laser engineering, electroacoustics, solid-state materials, devices, and intelligent systems engineering.

Credit(s): 1–6

This course consists of individual work on research problems for students enrolled in doctoral programs.

Credit(s): 1–12

This course provides graduate students with continued support and advisement. It is usually taken following completion of all coursework required for the degree.

Credit(s): 1–9