EE - Electrical Engineering

Students work with faculty adviser to complete the first phase of a capstone project.

Students work with faculty adviser to complete the second phase of a capstone project.

Introduction to designing digital circuits. Topics include number systems, Boolean algebra, simplification of Boolean functions, design and analysis of combinational and sequential logic circuits, hierarchical design, and simulation of digital circuits. Fee: $125

Circuit elements and concepts. Ohm's and Kirchhoff's laws. Simple resistive circuits. Review of matrix algebra. Node voltage method using matrix equations. Superposition. Thevenin and Norton equivalent circuits. Maximum power transfer theorem. Capacitance and inductance. Natural and step response of first- and second-order circuits. Sinusoidal steady-state circuits. PSPICE is incorporated as a simulation software.

Introduction to continuous- and discrete-time signals and systems. Continuous- and discrete-time linear time-invariant systems. Convolution. Impulse and step response. Laplace transform. Fourier series and Fourier transform. Sampling. Z transform. MATLAB software is incorporated throughout.

Measurement experience with a variety of basic electrical instruments. The student engineer will verify many of the principles of electrical circuit theory. Fee: $50

Study of ethical and professional responsibilities in the area of electrical engineering. The impact of solutions related to electrical engineering in global, economic, environmental, and societal contexts. Students are expected to develop a career plan and gain awareness regarding the importance of lifelong learning skills.

Lumped vs. distributed electrical circuits. Transient response of lossless transmission lines. Sinusoidal steady-state waves on lossless transmission lines. Smith chart and impedance matching techniques and networks. Review of vector calculus. Maxwell's equations and solution of wave equations. Uniform plane electromagnetic waves in a simple unbounded lossless medium.

Introduction to digital systems. TTL and CMOS 74-series logic families. Register-transfer level (RTL) combinational and sequential circuit design principles and practices using 74-series devices. Overview of programmable logic device (PLD) architectures. Combinational and sequential circuit designs using a hardware description language. Fee: $75

Computer systems evolution. Processor to memory interface. Introduction to microcontrollers. Microcontroller instruction set architecture and assembly language programming. Parallel input/output device interfacing. Timers and interrupt handling. UART and Inter-IC (12C) serial communications. Analog-to-digital converter interface. Implementation of a microcontroller-based embedded system. Fee: $75

Basic concepts of electronic circuit analysis and design. Physical operation and modeling of diodes, Bipolar Junction Transistors and MOSFETs. Small-signal analysis of electronic circuits. Amplifier biasing and bias-point stability. Use of SPICE as a design tool.

EE 352 is a continuation of EE 351. It includes advanced analog circuit theory, analysis, and simulation using PSPICE. Topics include 1) BJT and MOS transistor amplifiers, 2) frequency response, 3) feedback and, 4) opamp active filters. EE 352 provides the theoretical foundation for the companion electronics laboratory course, EE 371.

Companion laboratory course to the EE 352 Electronics Circuits II lecture course. Students analyze, assemble, and test various electronic circuits. Students perform rigorous AC and DC measurements using state-of-the-art instrumentation and correlate results to theoretical analysis. Rigorous written reporting of laboratory results is required. Designated as a Writing in the Discipline course. Fee: $50

Familiarization with the laboratory equipment. Basic gate operations. Combinational logic design using SSI, MSI, and LSI logic devices. Logic design with programmable logic devices. Sequential logic circuits. MSI counters. Designated as a Writing in the Discipline course. Fee: $75

Introduction to analog and digital communication systems with emphasis on modulation, demodulation, encoding, decoding, and synchronization techniques used in wireless systems. Python is used to simulate communication systems and to write a software defined receiver (SDR) for a real RF signal.

Modeling and control of continuous-time control systems. Topics include feedback, transfer functions, responses in the time and frequency domains, stability, and compensation. Applications include manufacturing and robotics.

Introduction to Verilog-based design process. Hierarchical modeling methodology. Basic Verilog language structures for modeling digital hardware functions. Modules and ports. Gate-level modeling. Data flow modeling. Behavioral modeling. Tasks and functions. Useful modeling techniques in digital system design. Component timing and delay modeling. Logic synthesis with Verilog HDL.

Introduction to topics in testing of digital systems. Physical circuit failures and fault modeling. Fault simulation and fault coverage. Algorithms for automatic test pattern generation. Introduction to Built-in self test. Testing of sequential circuits. Test application and response processing techniques. Design for testability. Includes an advanced testing project.

This course covers techniques used to process digital signals in applications such as audio filtering and speech recognition. Topics include analog-to-digital and digital-to-analog conversions, aliasing, quantization, discrete-time signals and systems, discrete-time Fourier transform, Z-transform, and digital filter design. MATLAB is used to demonstrate concepts and to process real signals.

Introduction to the hardware and software used in real-time digital signal processing (DSP) systems. Topics include analog-to-digital and digital-to-analog converters, DSP chip architecture, and special software techniques such as frame-based processing, circular buffering, digital filters, and the Fast Fourier Transform. Students will implement real-time DSP systems using C language and will run them on a DSP board.

Applications of electrical engineering in recording and modifying neural activity of the brain. Topicsinclude basics of brain imaging techniques such as electroencephalography (EEG), magneticresonance imaging (MRI), and functional magnetic resonance imaging (fMRI). Introduction to treatmentmethods utilizing electric and magnetic fields to alter brain activity such as repetitive transcranialmagnetic stimulation (rTMS).

A major design experience based on the knowledge and skills acquired in earlier course work and incorporating appropriate standards and multiple realistic constraints. Projects have some combination of the following characteristics: realism, communication, exposure, teamwork, learning, and related opportunities. 

Continuation of a major design experience based on the knowledge and skills acquired in earlier course work and incorporating appropriate standards and multiple realistic constraints. Projects have some combination of the following characteristics: realism, communication, exposure, teamwork, learning, and related opportunities. 

Selected study or project in electrical engineering for upper-division students. Must be arranged between the student and an individual faculty member and subsequently approved by the dean of engineering. No more than three hours of directed study taken at the University may be used for elective credits to satisfy degree requirements.

Credit Arranged.

Credit Arranged.

Faculty-directed student research. Before enrolling, a student must consult with a faculty member to define the project. May be repeated for credit. Course is graded A-F.

Introduction to analog and digital communication systems with emphasis on modulation, demodulation, encoding, decoding, and synchronization techniques used in wireless systems. Python is used to simulate communication systems and to write a software defined receiver (SDR) for a real RF signal. Knowledge of signals & systems is required.

Modeling and control of continuous-time control systems. Topics include feedback, transfer functions, responses in the time and frequency domains, stability, and compensation. Applications include manufacturing and robotics. Knowledge of Laplace transforms is required. A research paper on a relevant topic of interest is required.

Verilog-based design process. Hierarchical modeling methodology. Basic Verilog language structures for modeling digital hardware functions. Modules and ports. Gate level modeling. Dataflow modeling. Behavioral modeling. Tasks and functions. Useful modeling techniques in digital system design. Component timing and delay modeling. Logic synthesis with Verilog HDL. Advanced topics on high-level synthesis and system verification.

Introduction to topics in testing of digital systems. Physical circuit failures and fault modeling. Fault simulation and fault coverage. Algorithms for automatic test pattern generation. Introduction to Built-in self test. Testing of sequential circuits. Test application and response processing techniques. Design for testability. Includes an advanced testing project and a research paper.

Covers techniques used to process digital signals in applications (audio filtering, speech recognition, biomedical signal processing). Topics: analog-to-digital/digital-to-analog conversions, aliasing, quantization, discrete-time signals & systems, discrete-time Fourier transform, Z-transform, digital filter design. MATLAB used to demonstrate concepts and process real signals. Includes an advanced project to explore a digital signal processing system. Prior course in signals and systems recommended.

Hardware and software used in real-time digital signal processing systems. Analog-to-digital/digital-to-analog converters, DSP chip architecture, and software techniques including frame-based processing, circular buffering, digital filters, and Fast Fourier Transform. Implementation of real-time DSP systems using C language on a DSP board. Includes a project to explore a DSP system in detail. Recommended prior courses: signals & systems; C-language programming.

Credit arranged.

Credit arranged.

Credit arranged.

Faculty-directed student research. Before enrolling, a student must consult with a faculty member to define the project. May be repeated for credit. Course is graded A-F.

Credit arranged.