May be repeated once. 4 Hours. Topics include tools and techniques for practical visualization and elements of related fields, including computer graphics, human perception, computer vision, imaging science, multimedia, human-computer interaction, computational science, and information theory. Exercises are centered around a common embedded platform. Includes receiver noise and sensitivity; transmitter range; spurious emissions and IM distortion; antennae and propagation in the atmosphere; wireless standards; multiple-access techniques; and software-defined radio. 4 Hours. Covers the design and implementation of algorithms to solve engineering problems using a high-level programming language. Designed for students with primary interests in power conditioning, control applications, and electronic circuits, but it could prove useful for designers of high-performance computers, robots, and other electronic and electromechanical (mechatronic) systems in which the dynamical properties of power supplies become important. The resulting project is a tool capable of interpreting a subset of the C programming language and generating an executable program represented with MIPS assembly code. Courses are tailored toward technically or mathematically trained students. Discusses probability, random variables, random processes, and their application to noise in electrical systems. Includes a number of practical lab assignments that require students to apply their knowledge, as well as engage in a discussion of the current research in the field. Offered by the NSF Nanosystems Engineering Research Center for Translational Applications of Nanoscale Multiferroic Systems (TANMS) and co-taught by professors from UCLA, UC Berkeley, Cornell, California State University Northridge, and Northeastern University. Complete 16 semester hours from the course list. EECE 4646. Electrical Machines. 4.00 . Based on an integrative approach that requires minimal prerequisites: a junior-level course in signals and systems and some knowledge of electromagnetic field theory (possibly from physics classes), and does not require separate courses in electric machines, controls, or power electronics. Topics include vacuum technologies; vacuum pumps; vacuum system design and analysis; different thin film deposition technologies, including sputtering, chemical vapor deposition, electrochemical deposition, atomic layer deposition, etc. EECE 5698. Fundamentals of Engineering Algorithms. The university is a leader in experiential learning, powered by the world’s most far-reaching cooperative education program. Offers students an opportunity to obtain a fundamental understanding of the property and manipulation of light at the nanoscale. May be repeated without limit. Introduces analog integrated circuits (ICs) concepts with bipolar and field effect transistor devices. May be repeated up to four times. Includes an individual project where each student is expected to implement an application, port that application to several different styles of parallelism, and compare the results. Check the course site regularly for class materials and additional resources. EECE 5686. Introductory Directed Research in Electrical and Computer En... Healthcare Technologies: Sensors, Systems, and Analysis, Hardware-Software Codesign for FPGA-Based Systems. Please email nucopycenter@northeastern.edu for details. Reviews methods for dealing with both large and high-dimensional data sets, emphasizing distributed implementations. Acoustics and Sensing. 4 Hours. EECE 5652. Introduces analog-to-digital and digital-to-analog conversion concepts and the concepts of feedback and instability with applications to the design of amplifiers and oscillators. 4 Hours. Topics include service interfaces and peer-to-peer protocols, a comparison of the OSI (open system interconnection) reference model to the TCP/IP (Internet) and IEEE LAN (local area network) architectures, network-layer and transport-layer issues, and important emerging technologies such as Bluetooth and ZigBee. EECE 5638. Search, 360 Huntington Ave., Boston, Massachusetts 02115 • 617.373.2000 • TTY 617.373.3768 © 2020-2021 Northeastern University. This is where you would find the five-digit CRN to use when registering for classes. Then presents fundamentals of three-phase circuit analysis in the steady state, both for balanced and unbalanced operating conditions. 4 Hours. EECE 2412 and EECE 2413: Fundamentals of Electronics and Lab for EECE 2412: 5: EECE 2520: Fundamentals of Linear Systems: 4: EECE 2530 and EECE 2531: Fundamentals of Electromagnetics and Lab for EECE 2530: 5: Computer Engineering Fundamentals: If more than one computer engineering fundamentals course is taken, it can count as a technical elective. Offers an integrated lecture/lab course that covers the basics of the Unix operating system, high-level programming concepts, introductory digital design, wireless networking, and Simulink design. All EECE courses at Northeastern University (Northeastern) in Boston, Massachusetts. Continues EECE 4790. Computer vision brings together imaging devices, computers, and sophisticated algorithms to solve problems in industrial inspection, autonomous navigation, human-computer interfaces, medicine, image retrieval from databases, realistic computer graphics rendering, document analysis, and remote sensing. Develops students’ design capabilities of microprocessor-based control systems with input from sensory devices and output actuators by having teams of students design and implement a small mobile robot system to complete a specific task, culminating in a competition at the end of the course. Parallel Processing for Data Analytics. Simulation and Performance Evaluation. 4 Hours. Northeastern is proud to play a large role in educating tomorrow's leaders in this emerging area. Concentrates on silicon IC technology but also includes examples from other materials and device systems including microelectromechanical (MEMS) technologies that are used to build devices such as accelerometers, pressure sensors, and switches for telecommunications and other current examples provided from nanofabrication and nanotechnology. May be repeated up to two times. Dynamical Systems in Biological Engineering. Lectures cover relevant topics, including surveys of specific physical and cognitive disabilities and applicable engineering technologies. Presents numerical techniques used in solving scientific and engineering problems with the aid of digital computers. Northeastern University . Discusses metrics and benchmarking techniques used for evaluating performance. EECE 2210. EECE 5666. EECE 2150 - Circuits and Signal (167 Documents) EECE 2322 - Digital Logic Design (126 Documents) EECE 3468 - NOISE AND STOCHASTIC PROCESSES (100 Documents) EECE 2412 - Introduction to Electronics (66 Documents) Therefore, the goal of the electrical engineering and computer engineering programs is to help students develop these skills and provide the appropriate technical background for a successful career. Statistical Inference: An Introduction for Engineers and Data Analysts. Your user ID no longer exists. Emphasizes practical robot applications ranging from disaster response to healthcare to space exploration. Consists of a comprehensive laboratory performed by a team of students. Develops all concepts in the context of concrete biological applications, such as gene regulation, chemical reaction networks and stoichiometry, drug models and PK/PD, receptor/ligand interactions, synthetic constructs, action potential generation, enzymatic reactions, population interactions, epidemiology, epigenetic phenomena including differentiation, and transport, chemotaxis, and diffusion. Example: ENGW 3315. Examples emphasize concepts introduced in EECE 5580, such as system response to stimuli, stability, and robustness. Topicsinclude geometrical optics, polarized light, diffraction, andinterference. 5 Hours. EECE 7204 - Applied Probability and Stochastic Processes class wall and course overview (exams, quizzes, flashcards, and videos) at Northeastern (NU) 2020-21 Graduate PDF 617.373.4431 (fax). Presents basic topics (radio spectrum and its utilization, antennae, and information processing by modulation and demodulation). Thesis Option. EECE 4649. 4 Hours. Introduces fundamentals of statistical inference and data analysis through concepts of detection, estimation, and related signal processing algorithms. The schedule of classes lists all of the classes that are available for registration in a specific term. These are used in association with techniques and algorithms for dead reckoning and visual inertial odometry in conjunction with GPS and inertial measurement units. Several courses are also available 100% online, allowing you to tailor your coursework to your schedule. EECE 7337 - Information Theory . 2020-21 Undergraduate PDF Offers students an opportunity to design and implement a simple computer system on field-programmable logic using a hardware description language. Topics are selected by the instructor and vary from semester to semester. Introduces the analysis and design of classical control systems. These laboratory exercises require students to design, construct, and debug hardware and software that runs on an embedded platform. Special Topics in Computer Engineering. Access study documents, get answers to your study questions, and connect with real tutors for EECE 2210 : Electrical Engineering at Northeastern University. EECE 5642. Introduction to Software Security. Special topics include spatial frequency reuse; call blocking and cellular system capacity; power control and hand-off strategies; channel access and sharing; orthogonal frequency division multiplexing (OFDM—a modulation technique used in WLAN and the fourth-generation [4G] cellular systems) and spread spectrum modulation (third-generation WCDMA systems); diversity techniques and multi-input multi-output (MIMO) signal processing. 4 Hours. The laboratory, EECE2413, will be closely coordinated with the class material. Introduces combinatorial optimization, an emerging field that combines techniques from applied mathematics, operations research, and computer science to solve optimization problems over discrete structures. EECE 2530. Discussions will be conducted on Piazza.. Emphasizes MOS devices, which are currently the dominant technology in integrated circuits. Srinivas Tadigadapa, PhD Enabling Engineering. Begins with basic concepts such as CMOS device models, DC and small-signal analysis techniques for single- and multistage amplifiers, biasing configurations, and reference generation circuits. Addresses a set of analytical and practical problems, with emphasis on a rigorous theoretical treatment of relevant questions. Presents circuit-level designs of radio building blocks (resonators; L-C RF filters; crystals and IF filters; tuned transformers and impedance matching; amplifiers and power amplifiers; RF oscillators; mixers and up/down frequency conversion; signal detectors; and automatic gain control circuits). EECE 2160. EECE 5576. Develops the Fourier and Laplace transforms for the discussion of frequency-domain applications. Introduces robotics analysis covering basic theory of kinematics, dynamics, and control of robots. Accompanies EECE 2530. They also must work effectively in teams and communicate well. EECE 4632. Specific topics include HW/SW codesign, buses and interfacing, C as a hardware description language, high-level synthesis, pipelining, hardware memory hierarchies, and computer arithmetic. Provides an introduction to processing and analysis of digital images with the goal of recognition of simple pictorial patterns. Covers the structure and implementation of a modular compiler. You can recover your data by answering these questions. Addresses concepts such as hypothesis testing, Bayesian principles, likelihood functions, sufficient statistics, optimal estimation, and prediction. EECE 5554 - Robotics Sensing and Navigation . BS, MS, and PhD degrees are offered in both electrical and computer engineering. Programming is done in variants of the C programming language. Expects students to evaluate progress with interim milestone reports and to present the final design project with written and oral reports. Investigates the what (modeling), how (design), and why (analysis) of assistive robotics through the use of model-based design process. Electrical and Computer Engineering Capstone 2. Includes example data-oriented applications taken from multiple science/engineering disciplines and applies linear algebra and probability to analyze actual data sets. The first part of the course covers general aspects of wireless sensor networking, including protocol design, modeling, and simulation at all layers of the communication stack. Microwave Circuits and Networks. Numerical Methods and Computer Applications. May be repeated without limit. BS in Math + EECE 2150, EECE 2160, EECE 2412, EECE 2413, two of the following: EECE 2322 (with EECE 2323), EECE 2540, or EECE 2560 (COS) MS in Electrical and Computer Engineering, Concentration in Computer Networks and Security myNortheastern • Topics covered include number systems, data representation, a review of combinational and sequential digital logic, finite state machines, arithmetic-logic unit (ALU) design, basic computer architecture, the concepts of memory and memory addressing, digital interfacing, timing, and synchronization. Focuses on techniques to efficiently design and make use of field-programmable gate arrays (FPGAs) to accelerate applications. Topics include transmission lines: transmission line model with distributed circuit elements, transmission line equations and solutions, one-dimensional traveling and standing waves, and applications; electromagnetic field theory: Lorentz force equations, Maxwell’s equations, Poynting theorem, and application to the transmission line’s TEM waves. Introduces topics such as image formation, segmentation, feature extraction, matching, shape recovery, dynamic scene analysis, and object recognition. Emphasizes presenting fundamental concepts, essential mathematical formulas and theorems, and engineering applications. Covers the fundamentals of vacuum technology, thin film deposition technologies, characterization technologies, their applications in different industries, and the frontiers of research activities on thin film deposition technologies. Communications Systems. To thrive in Silicon Valley, Agarwal knows that Northeastern has to be nimble, ready to offer courses in subjects such as machine learning, augmented reality and Internet of Things (IoT). A large component of the class involves programming in both the ROS and LCM environments with real field robotics sensor data sets. Topics vary and include computer simulation, digital computer control, and use of CAD packages such as MATLAB for analysis and design of control systems. The goal of computer vision is to make useful decisions about real physical objects and scenes based on sensed images. Introduces basic concepts of digital communication over additive white Gaussian noise (AWGN) channels. 4 Hours. 4 Hours. 4.00 . 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