Electrical Engineering
Graduate Programs
Description
Master of Science in Electrical and Computer Engineering (MSECE)
(Thesis track: 32 cr; Design project track: 32 cr; Course work track: 32 cr)
A Master of Science in Electrical and Computer Engineering (MSECE) allows students to complete advanced study in various areas of electrical engineering and computer engineering. The program prepares students for various industry positions requiring or benefiting from additional competency in various areas of electrical engineering and computer engineering and provide a degree suitable for those interested in pursuing a doctoral program in engineering.
The program is designed to serve: engineers in business and industry who want to continue their formal engineering education at the postgraduate level of electrical and computer engineering; new engineering graduates who want to increase their depth of knowledge and develop an area of specialization; those graduates from other related science and engineering disciplines who want to broaden their backgrounds by pursuing electrical and computer engineering studies at the graduate level.
Students are allowed flexibility in the design of their own program of study by choosing courses from Electrical Engineering, Computer Engineering, Mechanical Engineering, Civil Engineering, Physics, Mathematics, Modeling and Simulation, Statistics, and Computer Science. Courses from other programs may be utilized toward the degree if approved by the student's graduate committee and advisor.
Majors |
Program | Locations | Major / Total Credits |
|---|---|---|---|
| Electrical and Computer Engineering MS | MS - Master of Science |
|
32 / 32 |
| Engineering MS | MS - Master of Science |
|
32 / 32 |
Policies & Faculty
Policies
Admission: Applicants to the electrical and computer engineering program must meet the general admission requirements of the College of Graduate Studies. A BS in Electrical or Computer Engineering or a closely related field from an accredited program with a minimum cumulative GPA of 3.0 on a 4.0 scale is required. International applicants must complete either the TOEFL, IELTS or Duolingo. A TOEFL score of at least 79; or, at least 6.5 overall band score if taking the IELTS; or, a Duolingo score of at least 105, is required.
Financial Assistance: A limited number of graduate teaching assistantships are available for those individuals with substantial laboratory experience in Electrical or Mechanical Engineering or related fields. Research assistantships may be available to exceptional candidates. Half-time and quarter-time assistantships include tuition waivers (18 credits maximum). It is recommended that applications for financial assistance be made by February 28 because announcements are typically made prior to the end of April for the Fall semester.
Contact Information
242 Trafton Science Center N
Department of Electrical & Computer Engineering and Technology
https://cset.mnsu.edu/ecet
Faculty
Chair
- Xuanhui Wu, Ph.D.
Program Coordinator
- Qun Zhang, Ph.D.
Faculty
500 Level
Credits: 4
.Prerequisites: none
Credits: 3
Overview of accounting and finance and their interactions with engineering. Lectures include the development and analysis of financial statements, time value of money, decision making tools, cost of capital, depreciation, project analysis and payback, replacement analysis, and other engineering decision making tools.Prerequisites: none
Credits: 3
Fundamentals of RF, microwave, and optical communication systems. Advances information theory. Digital modulation techniques. Phase-lock loop receivers and frequency synthesizers. Characterization of digital transmission systems. Equalization. Synchronization. Coding. Data compression. Nonlinear system analysis. Amplitude and phase distortion. AM-PM conversation. Intermodulation and cross-modulation. Advanced spread spectrum systems.Prerequisites: none
Credits: 3
A study of finite-state machine design, hardware description language, processor datapath design, principles of instruction execution, processor control design, instruction pipelining, cache memory, memory management, and memory system design.Prerequisites: none
Credits: 2
.Prerequisites: none
Credits: 3
The features, data rate, frequency range, and operation of several wireless networking protocols such as Wi-Fi, Low Energy Bluetooth, Near Field Communication, Radio frequency Identifier (RFID), Threads, and ZigBee that can be used to implement Internet of Things (IoT) are introduced. The electrical, functional, and procedural specifications of Wi-Fi are then examined in detail. The programming and data transfer using the hardware Wi-Fi kit are carried out to demonstrate the versatility of this protocol.Prerequisites: none
Credits: 3
Develops design and analysis techniques for continuous and discrete time control systems, including pole placement, state estimation, and optimal control.Prerequisites: none
Credits: 3
Develops design and analysis techniques for discrete signals and systems via Z-transforms, implementation of FIR and IIR filters. The various concepts will be introduced by the use of general and special purpose hardware and software for digital signal processing.Prerequisites: none
Credits: 3
Power generation, transmission and consumption concepts, electrical grid modeling, transmission line modeling, electric network power flow and stability, fault tolerance and fault recovery, economic dispatch, synchronous machines, renewable energy sources and grid interfacing.Prerequisites: none
Credits: 4
Principles, design and analysis of electrical power conversion and control systems, including the use of software tools for modeling, simulation and analysis of power electronic systems.Prerequisites: none
Credits: 3
Introduction to theory and techniques of integrated circuit fabrication processes, oxidation, photolithography, etching, diffusion of impurities, ion implantation, epitaxy, metallization, material characterization techniques, and VLSI process integration, their design, and simulation by SUPREM. Must be taken concurrently with EE 580.Prerequisites: none
Credits: 3
Principles of electromagnetic radiation, antenna parameters, dipoles, antenna arrays, long wire antennas, Microwave antennas, Mechanisms of radiowave propagation, scattering by rain, sea water propagation, guided wave propagation, periodic structures, transmission lines, Microwave millimeter wave amplifiers and oscillators, MIC & MMIC technology.Prerequisites: none
Credits: 2
.Prerequisites: none
Credits: 1-4
.Prerequisites: none
Credits: 3
Magnetic and superconducting properties of materials, microscopic theory of superconductivity, and tunneling phenomenon. Josephson and SQUID devices, survey of computer memories, memory cell and shift register, A/D converters, and microwave amplifiers. Integrated circuit technology and high temperature superconductors.Prerequisites: none
Credits: 1
Introduction to integrated circuit fabrication processes, device layout, mask design, and experiments related to wafer cleaning, etching, thermal oxidation, thermal diffusion, photolithography, and metallization. Fabrication of basic integrated circuit elements including PN junction, resistors, MOS capacitors, BJT and MOSFET in integrated form. Use of analytic tools for in-process characterization and simulation of the fabrication process by SUPREM. Must be taken concurrently with EE 575.Prerequisites: none
Credits: 1
Laboratory to accompany EE 584 VLSI design. Individual IC design projects will be assigned using IC layout tools and simulation software. Culminates in a group project fabrication under MOSIS. Must be taken concurrently with EE 584.Prerequisites: none
Credits: 3
This course covers cutting-edge areas of the study in smart grid and power systems. This course will cover fundamentals of power flow calculation, wind power and its integration, solar power and its integration, distributed generation sources, energy storage devices and electric vehicles. The basic ideas of the integration of microgrid with distribution networks, the demand response and demand side management, and electricity market will be introduced. Moderate work of programming in professional power systems software tools, PowerWorld and PSCAD will be required.Prerequisites: EE 333
Credits: 3
VLSI technology. MOS and Bipolar transistor theory, SPICE models. Transistor structure and IC fabrication processes; layout design rules. Custom CMOS/BICMOS logic design and layout topologies; cell layout/chip partitioning/clocking. Bipolar/MOS analog circuit design and layout. Group design project. Library research study. Must be taken concurrently with EE 581.Prerequisites: none
Credits: 4
This course focuses on CMOS Application Specific Integrated Circuit (ASIC) design of Very Large Scale Integration (VLSI) systems. The student will gain an understanding of issues and tools related to ASIC design and implementation. The coverage will include ASIC physical design flow, including logic synthesis, timing, floor-planning, placement, clock tree synthesis, routing and verification. An emphasis will be placed on low power optimization. The focus in this course will be Register-transfer level (RTL) abstraction using industry-standard VHDL/Verilog tools.Prerequisites: none
Credits: 4
The students will learn and practice advance level PLC programming knowledge in the Industrial Automation LAB. Learn programming and implementation of servo drive, VFD, Human Machine Interface (HMI) programming, Cognex vision system and controlling in a close loop with Allen Bradley ControlLogix PLC hardware.Prerequisites: none
Credits: 4
This course introduces students the recent advances in real-time embedded systems design. Topics cover real-time scheduling approaches such as clock-driven scheduling and static and dynamic priority driven scheduling, resource handling, timing analysis, inter-task communication and synchronization, real-time operating systems (RTOS), hard and soft real-time systems, distributed real-time systems, concepts and software tools involved in the modeling, design, analysis and verification of real-time systems.Prerequisites: none
Credits: 3
Machine Learning (ML) is the study of algorithms that learn from data, and it has become pervasive in technology and science. This course is an introductory course on the application of Artificial intelligence (AI) & ML in the field of Electrical and Computer Engineering. The course has three units. The first unit introduces several ML algorithms and Python programming languages. The second unit deals with autonomous driving. The last part deals with AI & ML-based wireless network design.Prerequisites: none
Credits: 1-4
Individual studies of problems of special interest. Open only to advanced students.Prerequisites: none
Credits: 1-6
.Prerequisites: none
600 Level
Credits: 3
Application of EE computer modeling and simulation tools. Design of experiments, Taguchi methods, automated data acquisition, and analysis methods.Prerequisites: none
Credits: 3
This course covers the analysis of continuous and discrete multivariate systems, linear models of stochastic and non-stochastic systems, and analog and digital sampled data systems. Issues examined include controllability, stability, observability, tensor properties, signal spectra, state equations, optimization, and computer simulation. A variety of case studies of advanced systems also examined.Prerequisites: none
Credits: 3
This course covers the analysis of non-linear continuous and discrete systems and devices. Topics covered include non-linear circuit analysis, non-linear stochastic and non-stochastic system models, limit cycles, oscillators, stability, non-linear wave functions. Computer simulation will be utilized in conjunction with selected case studies in advanced non-linear systems.Prerequisites: none
Credits: 3
Study of major paradigms used in the evaluation and execution of algorithms. Algorithm analysis will include complexity measure, hardware requirements, organization and storage system requirement.Prerequisites: none
Credits: 3
A treatment of computer architecture covering new technological developments, including details of multiprocessor systems. Special emphasis will be devoted to new concepts. Architectures of FPGAs and CPLDs will be explored and Hardware Description Languages such as VHDL and VERILOG will be used in project assignments.Prerequisites: none
Credits: 3
Computer architecture for parallel processors designed for high computation rates. Primary emphasis is on image processing, pattern recognition, etc. Performance of various systems with regard to interconnect network, fault tolerance, and programming.Prerequisites: none
Credits: 3
This course covers the programming model of a contemporary microprocessor/microcontroller. The course encompasses the interfacing and application of parallel and serial I/O devices using the parallel and serial ports such as SPI, I2C, and CAN. Industrial standard interface such as USB and Ethernet would be discussed. Development tools would be reviewed and used in projects. Multi-tasking and real-time kernal would be presented and projects would be assigned. Memory technologies and expansion issues would be reviewed and taught.Prerequisites: none
Credits: 3
Programmable logic design, simulation, synthesis, verification, and implementation using a Hardware Description Language (HDL), industry standard tools, and prototyping hardware. Mixed-level modeling including gate-level, dataflow and behavioral levels. HDL language constructs and design techniques. Logic timing and circuit delay modeling. Programming Language Interface (PLI). Advanced verification techniques.Prerequisites: none
Credits: 3
Study the ZigBee and IEEE 802.15.4 wireless specifications and develop embedded products with wireless communication capabilities for sensor intensive and control applications. An 8-bit or a 16-bit microcontroller will be used to implement the target hardware and software.Prerequisites: none
Credits: 3
Wave equations, solutions, wave propagation and polarization, reflection and transmissions, rectangular wave guides and cavities, strip line and microstrip lines, and geometric theory of diffraction.Prerequisites: none
Credits: 3
Active and passive microwave devices, microwave amplifiers and oscillators, mircowave filters, cavity resonators, microwave antennas, microwave receivers, microwave transmitters.Prerequisites: none
Credits: 3
Coherent and incoherent radiation, optical resonators, laser oscillators and amplifiers, propagation in optical fibers, integrated optical dielectric wave guides, semiconductor lasers, wave propagation in anisotropic, and non linear media, detection and noise.Prerequisites: none
Credits: 3
Selected topics in the theory of probability and statistics. Spectral analysis. Rayleigh, Rician, Gaussian, and Poisson processes. Noise figure. Signal-to-noise ratio requirements for analog and digital communications, remote sensing, radar and sonar. Random signals in linear and nonlinear systems. Signal-to-noise enhancement techniques. Source encoding. Shannon's theorems.Prerequisites: none
Credits: 3
Digital communication system modulation techniques. A/D conversion. Additional noise sources from sampling and encoding. Error detection and correction. Speech encoding. Data compression. Data networks. Companding. Multiplexing. Packet switching. Performance of digital baseband. Digital Signal Processing. Digital system design trade-offs.Prerequisites: none
Credits: 3
Principles of silicon integrated circuit fabrication processes and design limitations. Process modeling, crystal growth, oxidation, implantation, diffusion, deposition. Processing of bipolar and MOS devices and circuits. Photolithography and design rules. Introduction to GaAs technology. Use of SUPREME.Prerequisites: none
Credits: 3
Design and layout of passive and active electronic devices in silicon integrated circuits, both digital and analog. CMOS and bipolar circuit design principles will be developed. Assembly techniques and process control measurements and testing for yield control will be introduced.Prerequisites: none
Credits: 3
This course will introduce students to nanotechnology, and focus on the atomic conduction in material leading to the fundamentals of nanoscale transistors. Models for nanoscale devices, processes, and circuit considerations in the development of integrated circuits.Prerequisites: none
Credits: 3
Mathematical modeling of living systems. Entropy and information. Thermodynamic constraints. Feedback and feedforward mechanisms in metabolic processes. Metabolic heat generation and loss. Energy flow in living systems. Atomic and molecular bonds in biological systems. Engineering analysis of the cardiovascular, renal, immune, endocrine and nervous systems; analysis of specific disease states.Prerequisites: none
Credits: 3
Physiological transport phenomena (intercellular, intracellular and membrane transport), strength and properties of tissue, bioelectric phenomena, muscle contraction, cardiovascular and pulmonary mechanics, design of artificial organs, diagnostic tools, therapeutic techniques in the treatment of cancer, material compatibility problems in prosthetics, and ethical dilemmas in biomedicine.Prerequisites: none
Credits: 3
Fundamentals of RF, microwave, millimeter wave, and optical communication systems. Link power budgets. Bandwidth constraints. Phase-locked loop receivers. Matched filters. Spread spectrum communication systems. Modulation formats. Comparison of active and passive sensing systems. Signal processing.Prerequisites: none
Credits: 3
Students will be introduced to Statistical Signal Processing. Weiner filters and Adaptive filters will be studied. Methods of steepest descent algorithm and the least squares algorithm. Applications of these filters using special purpose software for digital signal processing.Prerequisites: none
Credits: 3
Develops analysis and design techniques for multivariable feedback systems. Definitions of poles and zeros of multivariable systems are established. Study of design methods such as LQG, Youla parametrization and H optimal control.Prerequisites: none
Credits: 1-4
Regular courses offered on demand by agreement with individual faculty members on an individual basis.Prerequisites: none
Credits: 3
Concepts of decision theory, utility theory and multi-person games. Cooperative and non-cooperative games, Nash equilibrium, zero and non-zero sum games, applications to robotics, networks, telecommunications, etc. Matrix payoff and matrix reduction methods.Prerequisites: none
Credits: 3
This course provides an overview of the challenges and techniques used for designing,constructing and controlling autonomous mobile robots. Topics include sensing techniques and technology, probabilistic robot localization, mapping, path planning techniques, motion planning, obstacle and collision avoidance, and multi-robot control.Prerequisites: none
Credits: 1-4
A course designed to upgrade the qualifications of persons on-the-job.Prerequisites: none
Credits: 1
Alternate plan paper preparation.Prerequisites: none
Credits: 1-5
Thesis research.Prerequisites: none
Credits: 1-4
Design project completion and design paper preparation.Prerequisites: none
Credits: 1-4
Varied topics in Electrical and Computer Engineering. May be repeated as topics change.Prerequisites: none
Credits: 1-4
Thesis preparation.Prerequisites: none
