Department of Electrical and Systems Engineering > Undergraduate Programs > Undergraduate Courses

# Undergraduate Courses

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Dept | # | Course Name :
[Course Description On]
| Credits |

ESE | 101 | Introduction to Engineering Tools: Matlab and Simulink | 1 |

Matlab and Simulink are important tools in quickly analyzing different designs in many engineering disciplines and are also perhaps the most used software in many engineering schools. Gain skills in the basics of the array-based language Matlab to write programs, including scripts and functions, to calculate and display variables and images. Learn the basics of Simulink to build and simulate models from standard blocks. Discover both Matlab and Simulink in an environment with supervised practice and hands-on experience. Practice problems are chosen from different engineering fields as well as from a few socio-economic fields so that students can see the software being exploited in real life applications. This is a pass/fail course. This course is open to all students, but preference will be given to freshmen students. | |||

ESE | 103 | Introduction to Electrical Engineering | 1 |

A hands-on introduction to electrical engineering to put the FUN into the electrical engineering FUNdamentals. Experiments are designed to be easy to conduct and understand. We will examine some of the technologies used in a variety of applications including the iPod, Ultrasound Imaging, Radar, and Credit Card Readers. We will also hear presentations from the EE faculty about their research. | |||

ESE | 141 | Introductory Robotics | 1 |

A hands-on introduction to robotics. Project-oriented course where students build and program a robot guided by upper-division students. Friendly competition at the end of semester. Students will gain electrical lab experience, programming experience, and a guided introduction into the field of robotics. | |||

ESE | 151 | Introduction to Systems Science and Engineering | 2 |

Introduction to the methodology of systems engineering: mathematical modeling, deterministic and stochastic systems, optimization, utilization of scientific literature. Applications in engineering, environmental studies, sports, medicine, business, etc. Guest lecturers from various disciplines. Students are required to do mini research projects (in groups) and present their results. Grading is based on presentations and reports. (Not open to seniors or graduate students.) Prerequisite: Math 132, Physics 117A. | |||

ESE | 230 | Introduction to Electrical and Electronic Circuits | 4 |

Electron and ion motion, electrical current and voltage. Electrical energy, current, voltage, and circuit elements. Resistors, Ohm's Law, power and energy, magnetic fields and dc motors. Circuit analysis and Kirchhoff's voltage and current laws. Thevenin and Norton transformations and the superposition theorem. Measuring current, voltage, and power using ammeters and voltmeters. Energy and maximum electrical power transfer. Computer simulations of circuits. Reactive circuits, inductors, capacitors, mutual inductance, electrical transformers, energy storage, and energy conservation. RL, RC and RLC circuit transient responses, biological cell action potentials due to Na and K ions. AC circuits, complex impedance, RMS current and voltage. Electrical signal amplifiers and basic operational amplifier circuits. Inverting, non-inverting, and difference amplifiers. Voltage gain, current gain, input impedance, and output impedance. Weekly laboratory exercises related to the lectures are an essential part of the course. Prerequisites: Phys 118A. Corequisite: Math 217. | |||

ESE | 232 | Introduction to Electronic Circuits | 3 |

Analysis and design of linear electronic circuits. Terminal characteristics of active semiconductor devices. Incremental and DC models for diodes, metal-oxide-semiconductor field effect transistors (MOSFETs), and bipolar junction transistors (BJTs). Design and analysis of single- and multi-stage amplifiers. Volatile and non-volatile semiconductor memories. Understanding of common application circuits in integrated circuit chips. Semester-long design project (e.g., designing circuits to process corrupted audio files). Prerequisite: ESE 230. | |||

ESE | 251 | Introduction to Systems Science and Engineering | 2 |

Introduction to the methodology of systems engineering: mathematical modeling, deterministic and stochastic systems, optimization, utilization of scientific literature. Applications in engineering, environmental studies, sports, medicine, business, etc. Guest lecturers from various disciplines. Students are required to do mini research projects (in groups) and present their results. Grading is based on presentations and reports. (Not open to seniors or graduate students.) Prerequisite: Math 132, Physics 117A. | |||

ESE | 260 | Introduction to Digital Logic and Computer Design | 3 |

Introduction to design methods for digital logic and fundamentals of computer architecture. Boolean algebra and logic minimization techniques; sources of delay in combinational circuits and effect on circuit performance; survey of common combinational circuit components; sequential circuit design and analysis; timing analysis of sequential circuits; use of computer-aided design tools for digital logic design (schematic capture, hardware description languages, simulation); design of simple processors and memory subsystems; program execution in simple processors; basic techniques for enhancing processor performance; configurable logic devices. Prerequisites: CSE 131/CS 101G or 126/136G or comparable programming experience. | |||

ESE | 297 | Introduction to ESE Undergraduate Research Projects | 2 |

This course is offered to students at all levels from all departments. The course is designed to give students some hands-on experience by implementing projects that use the lab PCs, the sbRIO robots from National Instruments, acoustic sensors, bio-medical sensors and 3D cameras. These projects are implemented in LabVIEW and Matlab and should prepare the students to work on topics that include the Robotic Sensing Undergraduate Research Projects in subsequent semesters. Note that under ESE 497 Undergraduate Research, students may select the Robotic Sensing Projects as well as other projects. Working in groups, students will implement algorithms that run on PCs and our wireless robotic platforms to track a moving audio source. Also, they will use an EEG system to implement a Brain Computer Interface (BCI) project and work with the new Kinect camera from Microsoft. Corequisite: CSE131 or equivalent | |||

ESE | 318 | Engineering Mathematics A | 3 |

Laplace transforms; matrix algebra; vector spaces; eigenvalues and eigenvectors; vector differential calculus and vector integral calculus in three dimensions. Prerequisites: Math 233 and Math 217 or their equivalents. | |||

ESE | 319 | Engineering Mathematics B | 3 |

Power series and Frobenius series solutions of differential equations; Legendre's equation; Bessel's equation; Fourier series and Fourier transforms; Sturm-Liouville theory; solutions of partial differential equations; wave and heat equations. Prerequisites: Math 233 and Math 217 or their equivalents. | |||

ESE | 326 | Probability and Statistics for Engineering | 3 |

Study of probability and statistics together with engineering applications. Probability and statistics: random variables, distribution functions, density functions, expectations, means, variances, combinatorial probability, geometric probability, normal random variables, joint distribution, independence, correlation, conditional probability, Bayes theorem, the law of large numbers, the central limit theorem. Applications: reliability, quality control, acceptance sampling, linear regression, design and analysis of experiments, estimation, hypothesis testing. Examples are taken from engineering applications. Prerequisites: Math 233 or equivalent. | |||

ESE | 330 | Engineering Electromagnetics Principles | 3 |

Electromagnetic theory as applied to electrical engineering: vector calculus; electrostatics and magnetostatics; Maxwell's equations, including Poynting's theorem and boundary conditions; uniform plane-wave propagation; transmission lines, TEM modes, including treatment of general lossless lines, and pulse propagation; introduction to guided waves; introduction to radiation and scattering concepts. Pre-requisite: (1) 317 En Math or (2) Pre-requisite: ESE 318 En Math A and Co-requisite: ESE 319 En Math B. | |||

ESE | 332 | Power, Energy, and Polyphase Circuits | 3 |

Fundamental concepts of power and energy; electrical measurements; physical and electrical arrangement of electrical power systems; polyphase circuit theory and calculations; principal elements of electrical systems such as transformers, rotating machines, control, and protective devices, their description and characteristics; elements of industrial power system design. Prerequisite: ESE 230. | |||

ESE | 351 | Signals and Systems | 3 |

Introduction to concepts and methodology of linear dynamic systems in relation to discrete- and continuous-time signals. Representation of systems and signals. Fourier, Laplace, and Z-transforms and convolution. Input-output description of linear systems: impulse response, transfer function. State-space description of linear systems: differential and difference equation description, transition matrix. Time-domain and frequency-domain system analysis: transient and steady-state responses, system modes, stability, frequency spectrum. System design: filter, modulation. Continuity is emphasized from analysis to synthesis and implementation. Use of Matlab. Prerequisites: The notion of Matrix algebra and Math 217 or equivalent, Physics 117A-118A Physics 117A-118A Corequisite: ESE 318 or 317. | |||

ESE | 400 | Independent Study | 3 |

Opportunities to acquire experience outside the classroom setting and to work closely with individual members of the faculty. A final report must be submitted to the department. Not open to first-year or graduate students. Consult adviser. Hours and credit to be arranged. | |||

ESE | 404 | Applied Operations Research | 3 |

Application of deterministic and stochastic operations research techniques to real-world problems. Emphasis is given to linear programming and simulation. The nature of the problems ranges from logistics and planning to operations management. The systems to be examined are transportation systems, supply chain systems, medical care delivery systems, urban service systems, management systems, manufacturing systems. Emphasis is placed on the problem formulation of real-world problems, the use of computer software and the analysis of the solutions. Prerequisites: ESE 326 and ESE 317 or equivalent. ESE 403 is not a prerequisite for this course and it is possible to take this course without ESE 403. | |||

ESE | 407 | Analysis and Simulation of Discrete Event Systems | 3 |

Study of the dynamic behavior of discrete event systems and techniques for analyzing and optimizing the performance of such systems. Covers both classical and recent approaches. Classical topics include Markov chains, queuing theory, networks of queues, related algorithms, and simulation methods. Recent approaches include decomposition and aggregation, approximation, and perturbation analysis of nonclassical systems. Applications are drawn from various areas, including production systems. Prerequisites: Math 217, ESE 326 or equivalent, CSE 126 or equivalent. | |||

ESE | 408 | A System Dynamics Approach to Designing Sustainable Policies and Programs | 3 |

Principles and practice of modeling dynamic systems in the sciences, engineering, social sciences, and business. Model structure and its relationships to prior knowledge and assumptions, measurable quantities, and ultimate use in solving problems in application areas. Problems considered are in the areas of intervention, policy-making, business, and engineering systems. Model verification. The basic theory and practice of system dynamics. Quantitative methods are emphasized. Senior or graduate standing. | |||

ESE | 415 | Optimization | 3 |

Optimization problems with and without constraints. The projection theorem. Convexity, separating hyperplane theorems; Lagrange multipliers, Kuhn-Tucker-type conditions, duality; computational procedures. Optimal control of linear dynamic systems; maximum principles. Use of optimization techniques in engineering design. Prerequisites: Math 309 and ESE 317 or ESE 318 or permission of instructor. | |||

ESE | 433 | Radio Frequency and Microwave Technology for Wireless Systems | 3 |

Focus is on the components and associated techniques employed to implement analog and digital radio frequency (RF) and microwave (MW) transceivers for wireless applications, including: cell phones; pagers; wireless local area networks; global positioning satellite based devices; and RF identification systems. A brief overview of system-level considerations is provided, including modulation and detection approaches for analog and digital systems; multiple-access techniques and wireless standards; and transceiver architectures. Focus is on RF and MW: transmission lines; filter design; active component modeling; matching and biasing networks; amplifier design; and mixer design. Prerequisite: ESE 330. | |||

ESE | 435 | Electrical Energy Laboratory | 3 |

Experimental studies of principles important in modern electrical energy systems. Topics include: AC power measurements, electric lighting, photovoltaic cells and arrays, batteries, DC-DC and DC-AC converters, and three-phase circuits. Each experiment requires analysis, simulation with MultiSim, and measurement via LabView and the Elvis II platform. Prerequisites: ESE 230 and 351 | |||

ESE | 437 | Sustainable Energy Systems | 3 |

We will survey the field of sustainable energy and explore contributions within electrical and systems engineering. Topics include introductory electric power systems, smart grids, and the roles of heat engines, photovoltaics, wind power, and energy storage, as well as analysis and optimization of energy systems. The course will consist of lectures, review and discussion of literature, and student projects. Prerequisite: ESE 317 or ESE 318 or ESE 319 and ESE 230 or ESE 351 or permission of instructor. | |||

ESE | 441 | Control Systems | 3 |

Introduction to theory and practice of automatic control for continuous-time systems. Representations of the system: transfer function, block diagram, signal flow graph, differential state equation and output equation. Analysis of control system components. Transient and steady-state performance. System analysis: Routh-Hurwitz, root-locus, Nyquist, Bode plots. System design: PID controller, and lead-lag compensators, pole placement via state feedback, observer, stability margins in Nyquist and Bode plots. Emphasis on design principles and their implementation. Design exercises with a MATLAB package for specific engineering problems. Prerequisites: ESE 351 or MASE 431. | |||

ESE | 446 | Robotics: Dynamics and Control | 3 |

Homogeneous coordinates and transformation matrices. Kinematic equations and the inverse kinematic solutions for manipulators, the manipulator Jacobian and the inverse Jacobian. General model for robot arm dynamics, complete dynamic coefficients for six-link manipulator. Synthesis of manipulation control, motion trajectories, control of single- and multiple-link manipulators, linear optimal regulator. Model reference adaptive control, feedback control law for the perturbation equations along a desired motion trajectory. Design of the control system for robotics. Prerequisites: ESE 351, knowledge of a programming language, and ESE 317 or 318; Co-requisite: ESE 441. | |||

ESE | 447 | Robotics Laboratory | 3 |

Introduces the students to various concepts such as modeling, identification, model validation and control of robotic systems. The course focuses on the implementation of identification and control algorithms on a two-link robotic manipulator (the so-called pendubot) that will be used as an experimental testbed. Topics include: Introduction to the mathematical modeling of robotic systems; nonlinear model, linearized model; Identification of the linearized model: input-output and state-space techniques; Introduction to the identification of the nonlinear model: energy-based techniques; model validation and simulation; stabilization using linear control techniques; a closer look at the dynamics; stabilization using nonlinear control techniques. Prerequisite: ESE 351 or MAE 417. | |||

ESE | 448 | Systems Engineering Laboratory | 3 |

Experimental study of real and simulated systems and their control. Identification, input-output analysis, design and implementation of control systems. Noise effects. Design and implementation of control laws for specific engineering problems. Corequisite: ESE 441 and knowledge of a programming language. | |||

ESE | 449 | Digital Process Control Laboratory | 3 |

Applications of digital control principles to laboratory experiments supported by a networked distributed control system. Lecture material reviews background of real-time programming, data acquisition, process dynamics, and process control. Exercises in data acquisition and feedback control design using simple and advanced control strategies. Experiments in flow, liquid level, temperature, and pressure control. Term project. Prerequisite: ESE/ME 441 or equivalent. Co-requisite: ChE 462 or equivalent. | |||

ESE | 460 | Switching Theory | 3 |

Advanced topics in switching theory as employed in the synthesis, analysis, and design of information processing systems. Combinational techniques: minimization, multiple output networks, state identification and fault detection, hazards, testability and design for test are examined. Sequential techniques: synchronous circuits, machine minimization, optimal state assignment, asynchronous circuits, and built-in self-test techniques. Prerequisite: CSE 260M or equivalent. | |||

ESE | 462 | Computer Systems Design | 3 |

Introduction to modern design practices, including the use of FPGA design methodologies. Students use a commercial CAE/CAD system for VHDL-based design and simulation while designing a selected computation system. Prerequisites: CSE 361S and 362M. | |||

ESE | 467 | Embedded Computing Systems | 3 |

Introduces the issues, challenges, and methods for designing embedded computing systems - systems designed to serve a particular application, which incorporate the use of digital processing devices. Examples of embedded systems include PDAs, cellular phones, appliances, game consoles, automobiles, and iPod. Emphasis is given to aspects of design that are distinct to embedded systems. The course examines hardware, software, and system-level design. Hardware topics include microcontrollers, digital signal processors, memory hierarchy, and I/O. Software issues include languages, run-time environments, and program analysis. System-level topics include real-time operating systems, scheduling, power management, and wireless sensor networks. Students will perform a course project on a real wireless sensor network testbed. Prerequisites: CSE 361S. | |||

ESE | 471 | Communications Theory and Systems | 3 |

Introduction to the concepts of transmission of information via communication channels. Amplitude and angle modulation for the transmission of continuous-time signals. Analog-to-digital conversion and pulse code modulation. Transmission of digital data. Introduction to random signals and noise and their effects on communication. Optimum detection systems in the presence of noise. Elementary information theory. Overview of various communication technologies such as radio, television, telephone networks, data communication, satellites, optical fiber, and cellular radio. Prerequisites: ESE 351 and ESE 326. | |||

ESE | 497 | Undergraduate Research | 3 |

Undergraduate research under the supervision of a faculty member. A written final report and a Web page describing the research are required. | |||

ESE | 498 | Electrical Engineering Design Projects | 3 |

Working in teams, students address design tasks assigned by faculty. Each student participates in one or more design projects in a semester. Projects are chosen to emphasize the design process, with the designers choosing one of several paths to a possible result. Collaboration with industry and all divisions of the University is encouraged. Prerequisite: senior standing. | |||

ESE | 499 | Capstone Project | 3 |

Term design project supervised by a faculty course adviser. The project must require use of the theory, techniques, engineering, and concepts of the student's major: electrical engineering or systems science & engineering. The project must have a client, typically either an engineer or supervisor from local industry or a professor or researcher in university laboratories. Namely a self-directed project is not allowed. The solution of a real technological or societal problem is carried through completely, starting from the stage of initial specification, proceeding with the application of engineering methods, and terminating with an actual solution. Required documents are a written proposal, a final report, and a Web page on the project. An oral presentation of the project also is required. Prerequisite: ESE senior standing and instructor's consent. |