Courses
The listing of a course description here does not guarantee a course’s being offered in a particular term. Please refer to the published schedule of classes on the MyBU Student Portal for confirmation a class is actually being taught and for specific course meeting dates and times.
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ENG EC 415: Software Radios
Enrollment Requirements: Undergraduate Prerequisite: ENGEK 381; Graduate Prerequisite: Graduate Standing
Signal analysis and transmission: amplitude modulation, angle modulation, pulse- amplitude and pulse-code modulation; amplitude shift-keying, frequency shift- keying, phase-shift keying. Case studies of practical communication systems. Includes lab. -
ENG EC 417: Electric Energy Systems: Adapting to Renewable Resources
Enrollment Requirements: Undergraduate Prerequisite: ENGEK 307; or LEAP Program students
This course will present a detailed perspective of electric power systems from generation, transmission, storage, to distribution to end users. Significant emphasis will be placed on methodologies for reliable and efficient transmission and distribution of power over the grid including challenges for adapting to renewable resources such as photovoltaics and wind. Conventional approaches will be presented with emphasis to future technology such as the "smart grid". Analysis of 3-phase power will be presented using numerous examples. Items such as power system stability, security, reliability will be covered. Optimization methods, models, simulation techniques, monitoring and control, grid storage technologies, and micro-grids will also be discussed. Power electronics will be introduced specifically in reference to high voltage circuits. Finally, planning for large numbers of electric vehicles will present new challenges to the effective distribution of power which will be discussed from both centralized and decentralized approaches. -
ENG EC 418: Introduction to Reinforcement Learning
Enrollment Requirements: Undergraduate Prerequisite: ENGEK 381 or (CDSDS 120 and CDSDS 121 and CDSDS 122); or LEAP Program students
Reinforcement learning is a subfield of artificial intelligence which deals with learning from repeated interactions with an environment. Reinforcement learning is the basis for algorithms for playing strategy games such as Chess, Go, Backgammon, and Starcraft, as well as a number of algorithms throughout robotics, operations research, and other fields of engineering. This course will cover the fundamental algorithms of reinforcement learning, focusing on the core principles underlying these methods. Topics covered will include Dynamic Programming, Markov Decision Processes, Value Iteration, Policy Iteration, Temporal Difference Methods and Monte Carlo, Function Approximation in Reinforcement Learning and Neural Networks -
ENG EC 427: Software Engineering in Practice
Enrollment Requirements: Undergraduate Prerequisite: ENGEC 327; or LEAP Program students
This class builds on students' software design skills by introducing them to an array of industry relevant concepts such as test driven development, effective understanding and debugging of existing codebases, use of IDEs, re-factoring, source control management, microservice architecture, interservice communication, continuous deployment, data storage, fault tolerance and isolation, and system scaling. -
ENG EC 440: Introduction to Operating Systems
Enrollment Requirements: Undergraduate Prerequisite: ENGEC 327; or LEAP Program students
Operating system concepts and design objectives. Concurrent processes, process synchronization, and deadlocks. Resource management including virtual memory, CPU scheduling, and secondary storage. File structures, input/output, and distributed systems. Case studies of popular operating systems. -
ENG EC 441: Introduction to Computer Networking
Enrollment Requirements: Undergraduate Prerequisite: ENGEK 381; or LEAP Program students
Computer networks, focusing on the Internet. Application protocols (Web, E- mail), basics of socket programming, major Internet protocols (TCP and IP), fundamental aspects of routing and reliable data transfer over networks, medium access protocols, wired and wireless Local Area Networks (LANs) technologies. Hands-on laboratory modules on client-server programming, Internet experiments, and protocol implementation. Includes lab. -
ENG EC 444: Smart and Connected Systems
Enrollment Requirements: Undergraduate Prerequisite: ENGEC 311 and ENGEC 327; or LEAP Program students
Hands-on introductory course to cyber-physical and IoT systems. Microcontrollers: integrated development environments (ISEs), architecture, and I/O interfaces. Hardware interfacing of systems: formal design and specifications, real-time OS, programming, and control. IoT systems: smart phones, wireless personal area networks (WPANs), IP gateways, mobile cloud computing, reliability, security, and privacy. Course culminates with a team project. -
ENG EC 447: Software Design
Object-oriented software design for desktop applications with a graphical user interface. C# and Microsoft .NET programming assignments. Provides a solid foundation in modern programming for engineering and other applications. -
ENG EC 451: Directed Study
Student may, under the supervision of a faculty member, undertake individual study of a subject relevant to electrical, computer, and systems engineering, if the subject is not covered in a regularly scheduled course. Tangible evidence of achievement must be submitted at the end of the semester. -
ENG EC 455: Electromagnetic Systems 1
Enrollment Requirements: Undergraduate Prerequisite: CASPY 212 and CASMA 226
Time varying electric and magnetic fields. Maxwell equations. Electromagnetic waves. Propagation, reflection, and transmission. Remote sensing applications. Radio frequency coaxial cables, microwave waveguides, and optical fibers. Microwave sources and resonators. Antennas and radiation. Radio links, radar, and wireless communication systems. Electromagnetic effects in high-speed digital systems. -
ENG EC 463: Senior Design Project 1
Enrollment Requirements: Undergraduate Prerequisite: ENGEK 210 and (CASWR 150 or CASWR 151 or CASWR 152 or CASWR 153 or KHCST 112)
Development of the technical, communication, personal, and team skills needed for successful design in electrical and computer engineering. Specifications and standards, information collection, design strategies, modeling, computer- aided design, optimization, system design, failure and reliability, human factors. Oral and written communication of technical information. Team dynamics and ethical issues in design. Design project for a small-scale electrical or computer system. Preparation of detailed proposals for senior design projects in the following semester. Includes lab. Effective Fall 2020, this course fulfills a single unit in each of the following BU Hub areas: Digital/Multimedia Expression, Writing-Intensive Course, Research and Information Literacy. -
ENG EC 464: Senior Design Project 2
Enrollment Requirements: Undergraduate Prerequisite: ENGEC 463
Continuation of a team project in an area of electrical and computer engineering, as proposed in EC 463. Application of technical, communication, personal, and team skills. Oral and written communication of technical information, including progress reports, technical memos, final report, and oral presentations. Includes lab. Effective Spring 2021, this course fulfills a single unit in each of the following BU Hub areas: Oral and/or Signed Communication, Writing-Intensive Course. -
ENG EC 467: Senior Thesis
Enrollment Requirements: Undergraduate Prerequisite: ENGEC 463
Well-prepared students may choose to do a formal senior thesis under the direct guidance of a departmental faculty member. Students selecting this option must obtain petitioned approval before the beginning of the semester of thesis registration. Effective Spring 2021, this course fulfills a single unit in each of the following BU Hub areas: Oral and/or Signed Communication, Writing-Intensive Course. -
ENG EC 491: Engineering with Light
Technologies that use light are all around us, both in well-established and rapidly developing areas. This introductory optics course aims for students to see the potential of optics in different engineering applications. Students will learn about progressively advanced models of light - geometric optics and imaging, wave optics with diffraction and interferometry applications, polarization, and use of light sources and detectors. Guest lectures and lab-visits will highlight modern engineering applications. Through optics laboratories, students will gain competence in designing, aligning, and troubleshooting optical systems to meet specified performance criteria. Students will present posters on course topics in their interest. -
ENG EC 500: Special Topics in Electrical and Computer Engineering
Enrollment Requirements: Undergraduate Prerequisite: Junior Standing or Senior Standing; Graduate Prerequisite: Graduate Standing
Specific prerequisites vary according to topic. Coverage of a specific topic in electrical, computer, or systems engineering. Subject varies from year to year and is generally from an area of current or emerging research. -
ENG EC 501: Dynamic System Theory
Enrollment Requirements: Undergraduate Prerequisite: CASMA 242 or ENGEK 103 or ENGME 404; Graduate Prerequisite: Graduate Standing
Introduction to analytical concepts and examples of dynamic systems and control. Mathematical description and state space formation of dynamic systems; modeling, controllability, and observability. Eigenvector and transform analysis of linear systems including canonical forms. Performance specifications. State feedback: pole placement and the linear quadratic regulator. Introduction to MIMO design and system identification using computer tools and laboratory experiments. Same as ENG ME 501 and ENG SE 501. Students may not receive credit for both. -
ENG EC 503: Introduction to Learning from Data
Enrollment Requirements: Undergraduate Prerequisite: ENGEK 381 and (ENGEK 125 or ENGEK 122 or CAS CS111); Graduate Prerequisite: Graduate Standing
This is an introductory graduate course in (classical) machine learning covering the basic principles and methods of four major non-sequential supervised and unsupervised learning problems namely, classification, regression, clustering, and dimensionality reduction. A variety of contemporary applications will be explored through homeworks and a project. -
ENG EC 504: Advanced Data Structures
Enrollment Requirements: Undergraduate Prerequisite: ENGEC 330; Graduate Prerequisite: Graduate Standing
Review of basic data structures and Java syntax. Data abstraction and object-oriented design in the context of high-level languages and databases. Design implementation from the perspective of data structure efficiency and distributed control. Tailoring priority queues, balanced search trees, and graph algorithms to real-world problems, such as network routing, database management, and transaction processing. -
ENG EC 505: Stochastic Processes
Enrollment Requirements: Undergraduate Prerequisite: ENGEK 381; Graduate Prerequisite: Graduate Standing
Introduction to discrete and continuous-time random processes. Correlation and power spectral density functions. Linear systems driven by random processes. Optimum detection and estimation. Bayesian, Weiner, and Kalman filtering. -
ENG EC 508: Wireless Communication
Enrollment Requirements: Undergraduate Prerequisite: ENGEK 381 and (ENGBE 403 or ENGEC 401); Graduate Prerequisite: Graduate Standing
Fundamentals of wireless communication from a physical layer perspective. Multipath signal propagation and fading channel models. Design of constellations to exploit time, frequency, and spatial diversity. Reliable communication and single-user capacity. Interference management, multiple-access protocols, and multi-user capacity. Cellular uplink and downlink. Multiple-antenna systems and architectures. Connections to modern wireless systems and standards.
