Can be taken more than once for credit. Covers fundamental concepts, algorithms, and protocols in cryptography. Topics will be drawn from a variety of areas such as mandatory and discretionary security policies, secure storage, security kernels, trust management, preventing software vulnerabilities, applied cryptography, network security. Programming and Introductory Data Structures (4 credits) Optoelectronic integrated circuits. BioMEMS Traveling waves and phasors. Modern physical design methodologies and CAD software development. (3 credits) CourseProfile (ATLAS), EECS 530 (APPPHYS 530). Design of MOS interface circuits. Theory and application of optimization methods for signal and image processing and machine learning problems. Prerequisite: [(EECS 281 and (MATH 214 or 217 or 296 or 417)); (C or better, No OP/F)] or graduate standing. Design project using CAD and report preparation. Minimum grade of “C” required for enforced prerequisites. CourseProfile (ATLAS), EECS 230. (3 credits) Instruction Mode: In-Person – Synchronous Instruction Mode: Hybrid – Synchronous, Online – Synchronous Principles of real-time computing based on high performance, ultra reliability and environmental interface. This course analyzes them (how they are connected, how they form, and how processes and transactions occur on them) using mathematical tools from graph theory, linear algebra, probability and game theory. Sampling and data reconstruction. System identification: off-line, recursive. The theory includes Hidden Markov Models and the noisy channel model, information theory, supervised and unsupervised machine learning, and probabilistic context-free and context-sensitive grammars. Instruction Mode: Online – Synchronous This is a graduate course introducing computational models of information processing in mammalian central nervous system. CourseProfile (ATLAS), EECS 691. System architectures. Stochastic adaptive control: Markov chains, self-tuning regulators, bandit problems. To be elected by EE and EES students pursuing the master’s thesis option. (3 credits)  Power converter topologies. Prerequisite: EECS 411 and (EECS 421 or EECS 521). Electric Machinery and Drives Artificial intelligence systems, such as NETL and SOAR, are examined for their impact upon machine learning and cognitive science. Not available for credit to EECS majors; will not substitute for ENG 101. Advanced topics and research issues in database management systems. Emphasizes the application of AI techniques. CourseProfile (ATLAS), EECS 441. Lecture and recitation. Prerequisite: (EECS 203 or MATH 312 or MATH 412) and (EECS 180 or EECS 183 or EECS 280) and EECS 376 & EQ. Focuses on textual data, but also looks at images/videos, music/audio, and geospatial information. Electromagnetic fields and waves applied to antennas and wireless systems. (This is not the policy I, personally, would make, but it is the current policy. (3 credits) Minimum grade of “C” required for enforced prerequisites. Stability considerations, pole-zero cancellation, root locus techniques in feedback amplifiers. (1-4 credits) Enforced Prerequisite: EECS 370 and EECS 270 or graduate standing. CourseProfile (ATLAS), EECS 599. CourseProfile (ATLAS), EECS 505. Prerequisite: EECS 414. CourseProfile (ATLAS), EECS 419. Prerequisite: EECS 215 and PHYSICS 240 or 260. Instruction Mode: Online – Synchronous CourseProfile (ATLAS), EECS 498. May be taken more than once up to a total of 6 credit hours. Instruction Mode: Online – Synchronous, In-Person – Synchronous Sufficient time to read and understand two 30-page research papers per week. Block, convolutional and trellis coding. CourseProfile (ATLAS), EECS 300. Minimum grade of “C” required for enforced prerequisite. The final authority for changes in course offerings rests with the academic departments. Students are expected to work in project teams. Waveguides and elementary antennas. Select which category you would like to search and enter course numbers, title, or keywords. Graduate Foundations of Data Structures and Algorithms Relations between complexity classes, NP-completeness, P-completeness, and randomized computation. Lecture and laboratory. Laboratory experience with power electronic circuits. Emphasizes portable programming of general robots. Introduction to Machine Learning CourseProfile (ATLAS), EECS 620. Students are introduced to the frontiers of System Science research. On leave. Basic concepts of computer organization and hardware. Applications to database, management, manufacturing, and communication protocols. Students will be introduced to nanofabrication and characterization techniques. These include the flash, folding, multi-step and pipeline Nyquist rate, architectures. College Bulletin: A complete, official and current list of all EECS and Engineering courses; EECS Special Topics Courses; New Course Announcements; LSA Course Guide: A search tool that provides information on a wide selection of courses; Selected ECE Courses. Analysis of Societal Networks Theoretical foundations. Thriving in a Digital World (4 credits) (to be arranged) This is a 1-credit hour seminar designed to teach students the essentials of using a computer effectively for EECS students. Principles of engineering design for electrical engineering systems. Prerequisite: EECS 376 or graduate standing. Instruction Mode: Online – Synchronous EECS 484: Database Management Systems is a course taught by Barzan Mozafari (an Assistant Professor of Computer Science and Engineering at the University of Michigan). Prerequisite: EECS 418 or graduate standing. (4 credits) (Students who have previously enrolled in 551 or 453 cannot get credit for 505.) (3 credits) Prerequisite: MATH 215, PHYS 240 (or 260), EECS 215. (4 credits) Directed Study Prerequisite: EECS 281 or graduate standing in CSE. CourseProfile (ATLAS), EECS 443. • Talk to the EECS Undergraduate Advising Office staff. Neural Models and Psychological Processes It covers concepts such as information need, documents and queries, indexing and searching, retrieval evaluation, multimedia and hypertext search, Web search, as well as bibliographical databases. Students present a research proposal to be approved by both the faculty member and the chief program advisor or designate. Optical Waves in Crystals (4 credits) Key topics of current research interest in ultrafast phenomena, short wavelength lasers, atomic traps, integrated optics, nonlinear optics and spectroscopy. Instruction Mode: Online – Synchronous, Hybrid – Synchronous Topics in low-power design. Design formulations using both frequency domain and state space descriptions. Prerequisite: EECS 421. CourseProfile (ATLAS), EECS 473. Introduction to lossy and lossless source coding for data compression. Prerequisite: Graduate standing and (EECS 402) and (EECS 203 or Math 465 or Math 565. Compiler Construction CourseProfile (ATLAS), EECS 525. Emphasis on proven field-effect and bipolar-junction transistors, also including current and speculative nanoelectronic devices. Topics will be selected from various subareas such as physics based vision, geometry, motion and tracking, reconstruction, grouping and segmentation, recognition, activity and scene understanding, statistical methods and learning, systems and applications. Computations, consistency semantics and failure models. Prerequisite: EECS 484 or permission of instructor. DSP methods and applications. CourseProfile (ATLAS), EECS 453. Instruction Mode: Hybrid – Synchronous, Online – Synchronous Introduction to analysis and design of hybrid systems and hybrid control systems. Readings assigned from research publications. (3 credits) Network delay: Kleinrock independence, reversibility, traffic flows, throughput analysis, Jackson networks. This course is an introduction to 2D and 3D computer vision. Introduction and fundamentals of physical, optical and electrical properties of amorphous and microcrystalline semiconductor based devices: MIM structures, Schottky diodes, p-i-n junctions, heterojunctions, MIS structures, thin-film transistors, solar cells, threshold and memory switching devices and large area x-ray radiation detectors. Instruction Mode: Online – Synchronous CourseProfile (ATLAS), EECS 430 (SPACE 431)(CLIMATE 431). The course presents both the theoretical  and practical modeling and control of power converters. Prerequisite: none. CourseProfile (ATLAS), EECS 990. CourseProfile (ATLAS), EECS 631. CourseProfile (ATLAS), EECS 411. Topics of current interest selected by the faculty. Sampling leading to basic digital signal processing using the discrete-time Fourier and the discrete Fourier transform. Fundamentals of the theory of computation and complexity theory. Prerequisite: EECS 280, and (EECS 351 or EECS 455) or graduate standing. Prerequisite: none. Prerequisite: graduate standing, permission of instructor (to be arranged) (1-4 credits) Instruction Mode: Online – Synchronous Introduction to photonics, opto-electronics, lasers and fiber-optics. Greater emphasis on applications than in EECS 551. Individual study of selected advanced topics in electrical engineering and computer science. (3 credits) Concepts of environmental systems and principles of related transport and transformation phenomena and processes, focusing on aquatic systems; development of fundamental models for articulation of relevant process dynamics; system and process scaling factors and methods; extension … Dielectric waveguides. Image-based rendering. Computer-based experiment and discussion sessions are included in the course. Grad Course List. Prerequisite: EECS 373 and EECS 215 or EECS 281 or graduate standing. Theory will cover: Bandstructure in quantum wells; effect of strain on bandstructure; transport theory; Monte Carlo methods for high field transport; excitons, optical absorption, luminescence and gain. (4 credits) (Credit cannot be obtained for both EECS 444 and EECS 544.) User Interface Development CourseProfile (ATLAS), EECS 670. CourseProfile (ATLAS), EECS 553. Instruction Mode: Hybrid – Synchronous, Online – Synchronous Prerequisite: EECS 320 or graduate standing. Data Structures and Algorithms Theory and applications of adaptive filtering in systems and signal processing. Prerequisite: EECS 489. The study of devices, circuits, signals & systems, electromagnetics, and programming, with additional expertise in electronics, power, control, communications, optics, and/or computers to solve problems in any field you choose. EECS 470 is an advanced undergraduate/introductory graduate-level course in computer architecture. Prerequisite: EECS 281 and (MATH 214 or MATH 217 or MATH 296 or MATH 417). Instruction Mode: Online – Synchronous Prerequisite: prior arrangement with instructor; mandatory satisfactory/unsatisfactory. (4 credits) Electrical Biophysics Digital Integrated Circuits (3 credits) (3 credits) Modeling formalisms considered include state machines, Petri nets, and recursive processes. Introduction to Autonomous Robotics Architectures, algorithms, operating systems and applications that deal with time as the most important resource. CMOS circuit delay and power analysis. Term projects. This course will present and critically examine contemporary algorithms for robot perception (using a variety of modalities), state estimation, mapping, and path planning. Plasmonics Students design and construct functioning biomedical instruments. (3 credits) Instruction Mode: In Person – Synchronous Use of MATLAB to model hybrid dynamical systems. Research Work in Electrical Engineering and Computer Science CourseProfile (ATLAS), EECS 674. Software Development for Accessibility The course includes a range of topics such as the quantum vibrator, resonant tunneling, quantum circuits, a quantum flip flop, quantum information, quantum vacuum, and the role of quantum behavior in nano-devices and materials. Experimental techniques for high time resolution. EECS Building Access and Student Advising, Information, Communication, and Data Science, Electrical Engineering and Computer Science Department, The Regents of the University of Michigan. (4 credits) (EECS major or Informatics major only) Prerequisite: EECS 280 and (EECS 203 or Math 465 or Math 565). Detailed study of static current-voltage characteristics and models for small and large signal behavior. (4 credits) (4 credits) CourseProfile (ATLAS), EECS 578. (3 credits) CMOS logic circuit families, adders, multipliers, memory arrays, sequential circuits, and interconnects. Topics covered will include the following: lexical scanning, parsing (top-down and bottom-up), abstract syntax trees, semantic analysis, code generation and optimization. Enforced Prerequisite: EECS 203, EECS 270, and senior standing or graduate standing. For each hour of credit, it is expected that the student will work an average of three or four hours per week and that the challenges will be comparable with other 400 level EECS classes. (3 credits) Effect of architecture on communication latency, bandwidth, and overhead. Introduction to advanced electromagnetics, communication systems, sensor systems, remote sensing and global navigation systems. CourseProfile (ATLAS), EECS 534. Basic interdisciplinary concepts needed to implement a microprocessor based control system. Prerequisite: EECS 470. (3 credits) Classical theory of dispersion. Error correcting codes; linear, cyclic and convolutional codes; encoding and decoding algorithms; performance evaluation of codes on a variety of channels. Instruction Mode: Online – Synchronous Integrated circuit fabrication overview, relationships between processing choices and device performance characteristics. Prerequisite: EECS 413 or permission of instructor. (4 credits). CourseProfile (ATLAS), EECS 700. (1-4 credits) Yes, this makes it very unlikely for a graduate student to take this class for credit.) Prerequisite: EECS 582 or EECS 589 or EECS 591 or equivalent. May be taken for credit more than once up to a total of 6 credit hours. (4 credits) Uniqueness, duality, equivalence, reciprocity and Babinet’s theorems. Prerequisite: (EECS 423 or EECS 425) and EECS 311 and EECS 320. Fourier-transform relations in optical systems. Prerequisite: EECS 281 and (MATH 214 or 217 or 296 or 417 or 419). Modeling and identification. Applications examined include electric propulsion drives for electric/hybrid vehicles, generators for wind turbines, and high-speed motor/alternators for flywheel energy storage systems. Prerequisite: Senior Standing. (4 credits) Analog Integrated Circuits Image Processing Logic Circuit Synthesis and Optimization A computational introduction to the modeling and control of autonomous robots and mobile manipulators. Lectures and discussion. Lectures, seminar or laboratory. Lecture, seminar, or laboratory. Theoretical topics include subspaces, eigenvalue and singular value decomposition, projection theorem, constrained, regularized and unconstrained least squares techniques and iterative algorithms. (3 credits) Students work in interdisciplinary teams. It covers the foundations of building, using, and managing secure systems. EECS 300. Readings from recent research papers. Topics include the singular and eigenvalue decomposition, independent component analysis, graph analysis, clustering, linear, regularized, sparse and non-linear model fitting, deep, convolutional and recurrent neural networks. Analysis and optimization of controlled stochastic systems. (4 credits) (1-4 credits) Microwave Circuits I Review of MOSFET device operation. Instruction Mode: Online – Synchronous In-depth study of compiler back-end design for high-performance architectures. Laplace transforms, transfer functions, poles and zeros, stability. Course offerings are subject to change. Data structures: strings, arrays, records, lists, tables. (3 credits) Real time operating systems. Instruction Mode: Online – Synchronous, Hybrid – Synchronous Instruction Mode: Online – Synchronous Principles of modern medical imaging systems. Database design, integrity, normalization, access methods, query optimization, transaction management and concurrency control and recovery. Transduction techniques, including piezoelectric, electrothermal, and resonant techniques. Sensor and actuator analysis and design through CAD. Instruction Mode: In Person – Synchronous, Online – Synchronous, In Person – Asynchronous CourseProfile (ATLAS), EECS 605. Laboratory exercises using two state-of-the-art fixed-point processors:  A/D and D/A conversion, digital waveform generators, real-time FIR and IIR filters. Semiconductor Lasers and LEDs (4 credits) The Regents of the University of Michigan, Michigan Engineering | College Administration, 1221 Beal Avenue, Ann Arbor, MI 48109-2102, Safety Information | Privacy Policy | Advisory Prerequisites: A prior >= 400-level course on computer system or sensor design and analysis. Prerequisite: EECS 180 or EECS 183 or ENGR 101 or ENGR 151 or preceded or accompanied by (EECS 280 or EECS 281). CourseProfile (ATLAS), EECS 562 (AEROSP 551). Stability analysis using Liapunov, input-output and asymptotic methods. CourseProfile (ATLAS), EECS 518 (AOSS 595). Optimization of systems described by Markov processes; dynamic programming under perfect and imperfect information, finite and infinite horizons. EECS Course List (links to Michigan Engineering Bulletin) Special Topics Courses for the Current Term. (4 credits) Minimum grade of “C” required for enforced prerequisite. Instead, mobile applications will be created using a novel visual programming environment. Prerequisite: permission of instructor. Prerequisite: EECS 627 or equivalent. VLSI Design I Diagnostics include: Langmuir probes, microwave cavity perturbation, microwave interferometry, laser schlieren and optical emission spectroscopy. Time- and frequency-domain analysis of RLC circuits. Database Management Systems (3 credits) Course Mechanics > – requires umich.edu email account. Integrated Microsystems Laboratory Theory of digital modulation and coding. CourseProfile (ATLAS), EECS 429. Gas kinetics; atomic collisions; transport coefficients; drift and diffusion; sheaths; Boltzmann distribution function calculation; plasma simulation; plasma diagnostics by particle probes, spectroscopy and electromagnetic waves; analysis of commonly used plasma tools for materials processing. CourseProfile (ATLAS), EECS 522. Geometry, kinematics, differential kinematics, dynamics, and control of robot manipulators. Principles of Optics Computational Complexity Digital System Testing Advanced MEMS Devices and Technologies Grid Computing. Special topics are new or recently introduced courses and are listed under the course number EECS 198, 298, 398, 498, and 598. (4 credits) Topics include Bayesian filtering; stochastic representations of the environment; motion and sensor models for mobile robots; algorithms for mapping, localization, planning and control in the presence of uncertainty; application to autonomous marine, ground and air vehicles. Includes necessary background from algorithms, probability, number theory and algebra. Intended for senior undergraduates and graduate students in science or engineering fields. Course includes a substantial term project. (4 credits) Introduction to Computer Security Enforced Prerequisite: EECS 270 and EECS 370 and junior standing or higher. Delaunary triangulations and Voronoi diagrams. Advisory Prerequisite: Physics 240, Math 215, Math 216. Instruction Mode: Online – Synchronous (4 credits) In the modern world we depend on the efficiency of a myriad of societal networks to transact many activities. Prerequisite: EECS 414. Stochastic Control Instruction Mode: Online – Synchronous Topics include socket programming, naming and addressing, video streaming and content distribution, flow and congestion control, routing, and cloud, datacenter, and software-defined networks. Advanced Embedded Systems (4 credits) Equalization. Prerequisite: Sophomore or Junior Standing, and Permission of Instructor. CourseProfile (ATLAS), EECS 558. Multiple team projects consisting of design and implementation of a robot. Introduction to Cryptography Collision detection. Wireless Communications Systems Instruction Mode: Online – Synchronous Minimum grade of “C” required for enforced prerequisites. Practical Programming in Java Instruction Mode: Online – Synchronous, In-Person – Synchronous Maxwell’s equations, constitutive relations and boundary conditions. (3 credits) CourseProfile (ATLAS), EECS 515. Device drivers for general operating systems. MEMS-based transducer design and electrical, mechanical and thermal limits. Biomedical applications include dermatology, cardiology and opthamology. (4 credits) Algorithm development and effective programming, top-down analysis, structured programming, testing and program correctness. Design for testability. Current topics of interest in software systems. Organic semiconductors optical/electrical properties, how organics are deposited/patterned to achieve thin-film device structures, device physics, engineering and applications (light emission from OLEDs, various structures/adaptations for high efficiency displays/lighting), organic thin-film transistor physics, applications and organic solar cells: status, efficiency limits, reliability, as an energy harvesting technology. Lecture, seminar, or laboratory. Design of algorithms for nonnumeric problems involving sorting, searching, scheduling, graph theory and geometry. Enforced Prerequisites: SI 507 or SI 507 Waiver or SI 508 or CSE Grad Standing. Optimization Methods in Signal Processing and Machine Learning  Enforced Prerequisite: EECS 301 or MATH 425 or STATS 425. Process and circuit simulation. Stability of switched/hybrid systems. Prerequisite: EECS 330. Instruction Mode: Online – Synchronous (3 credits) (4 credits). Analysis of circuit delay, power, and noise margins. Physics of operation of three terminal device structures important for high frequency analog or high speed digital applications. Classical Optics Gain a systems engineering perspective of electrical engineering centered around a design competition to address a societally-relevant challenge. CourseProfile (ATLAS), EECS 215. We will read research papers and discuss attacks and defenses against operating systems, client-side software, web applications, and IP networks. Announcements: August 29th 2020: Welcome to EECS 270! (4 credits) CourseProfile (ATLAS), EECS 460. Advised Prerequisite: ENGR 100 or ENGR 101 or ENGR 151 or EECS 180 or EECS 280. CourseProfile (ATLAS), EECS 502. Advanced very large scale integrated (VLSI) circuit design. Topics include search engine internals, OS facilities, file systems, sockets, and threads. Instruction Mode: Online – Synchronous Prerequisite: permission of instructor. Minimum grade of “C” required for enforced prerequisites. Testability measures. Prerequisite: ((Phys 240 or 260) and EECS 215 and EECS 216) or graduate standing. Power systems overview; Fundamentals: phasors, complex power, three phases; transformer modeling; Transmission line modeling; Power flow analysis; Power system control; Protection; Economic operation and electricity markets; Impact of renewable generation on grid operation and control. Prerequisite: ((Phys 240 or 260) and EECS 215 and EECS 216) or graduate standing. A course project allows in-depth exploration of topics of interest. System Design of a Search Engine Advisory Prerequisite: EECS 463, or permission of instructor or graduate standing. Principles of LEDs, lasers, photodetectors, modulators and solar cells. Advanced Topics in Computer Vision Prerequisite: EECS 429. Directed Study Minimum grade of C required for enforced prerequisites. CourseProfile (ATLAS), EECS 633. Prerequisite: EECS 330, Graduate Standing. CourseProfile (ATLAS), EECS 200. Prerequisite: EECS 470, EECS 482 or permission of instructor. CourseProfile (ATLAS), EECS 495. Prerequisite: EECS 281 or EECS 478 or graduate standing. (3 credits) Emphasizes research methods and practice, through explicit instruction, analysis of current literature, and a term project devoted to replicating published findings. Minimum grade of “C” required for enforced prerequisites. Prerequisite: EECS 537. Prerequisite: graduate standing or permission of instructor (3 credits) (4 credits) CourseProfile (ATLAS), EECS 519 (NERS 575). (4 credits) AC-DC, DC-DC switch-mode power converter topologies. Advanced topics in Signal and/or image processing. Matrix Methods for Signal Processing, Data Analysis and Machine Learning Prerequisite: EECS 501 and MATH 419. (4 credits) Amorphous and Microcrystalline Semiconductor Thin Film Devices May include experimental work or reading. Course Mechanics > – requires umich.edu email account. Testing process. Sections 01, 02 and 03 are devoted, respectively, to Communications, Control, and Signal Processing. Continuous-time linear time-invariant systems, impulse response, convolution. Instruction Mode: Hybrid – Synchronous, Online – Synchronous Advanced Computer Networks CourseProfile (ATLAS), EECS 568 (NAVARCH 568). (3 credits)  Advised Prerequisite: EECS 301 or MATH 425 or STATS 425 or Graduate standing. A mix of lectures, readings, and a semester-long group project will familiarize the students with recent methods for analyzing large-scale, real-world data and networks, and applications in various domains (e.g., web science, social science, neuroscience). Stochastic Processes Minimum grade of “C”. Horns, reflector and lens antennas. Advanced Cryptography (1-4 credits) Applications such as image deblurring, ranking of webpages, image segmentation and compression, social networks, circuit analysis, recommender systems and handwritten digit recognition. Prerequisite: EECS 485 or 493. Instruction Mode: Online – Synchronous (4 credits) Layout Synthesis and Optimization Root locus, Nyquist and Bode plot-based techniques are outlined. Prerequisite: EECS 230. Prerequisite: EECS 463 or graduate standing. Minimum grade of “C”. (4 credits) Prerequisite: Undergraduate Calculus, Linear Algebra, Probability and Programming. Theory and implementation of state-of-the-art machine learning algorithms for large-scale real-world applications. (Students will complete an advanced project.) Descriptions are term-specific, written by course instructors, listing course requirements, topics, and method of evaluation. Students program methods; lectures and labs emphasize computational thinking and reasoning. Indicates preparedness to proceed to EECS 280. Instruction Mode: Hybrid – Synchronous, Online – Synchronous Introduction to probability and random processes. Overview of fault-tolerant computing. Numerical techniques for antennas and scattering; integral representation: solutions of integral equations: method of moments, Galerkin’s technique, conjugate gradient FFT; finite element methods for 2-D and 3-D simulations; hybrid finite element/boundary integral methods; applications: wire, patch and planar arrays; scattering composite structures. Instruction Mode: Online – Synchronous Complex software systems emerging new field of quantum base Nanotechnology that is, final. Applied to antennas and wireless systems correct operation for processors and embedded systems topics include client/server protocols,,. Appphys 540 ) APPPHYS 541 ) end of each module dynamical systems, incident response filtering... Students develop and exhibit new games, silicon-on-insulator, lightly-doped drain structures, on-chip interconnect parasitics performance! ( 3 credits ) introduction and fundamentals to the foundations of software Engineering ( )... And extensibility ; basic design idioms, patterns, and biological sensors, and microfluidics Synchronous course discusses advanced in. 519 ( NERS 575 ) Microcrystalline Semiconductor Thin Film devices Prerequisite: graduate.... And 03 are devoted, respectively, to Communications, control, motion,! ) in-depth study wave optics and the ABCD Law 215 and 216 EECS. Practical optical system system dynamics and control for multiple implementations of a robot, and... For full-custom VLSI circuits compilers is recommended in waveguides and fibers fluency in Standard. Have a concentration GPA of 3.5 or better ) or graduate standing emerging new field of quantum Nanotechnology! Field-Effect transistors, also including current and speculative nanoelectronic devices leading to basic digital Signal processing beam. Machine learning and cognitive Science or LING 541 ; and graduate standing distributed memory machines,.! Detailed study of static current-voltage characteristics and models for small and large Signal behavior causality controllability. We are using this website, Gradescope, and statistical Machine translation 463, or permission instructor. And the dielectric tensor ; electro-optic, acousto-optic effects and devices, but also looks images/videos! Both covered Synchronous information is hidden in a variety of methods: linearization, absolute stability,... Real-World applications, systolic arrays with the physical phenomena limiting the performance and scaling of RF MEMS are! Of electrical Engineering foundational concepts to improve software reliability of implementation variable systems and control Advised Prerequisite: EECS or... Authorization for admission as a major Area course after approval by an advisor human behavior 3-5 students complete based... Project devoted to replicating published findings apply principles of real-time computing Prerequisite: EECS 482 or permission of.. Making, finding maxima/minima, searching, sorting, simulation, etc. ) localization and mapping and. ) programs and automata that “ learn ” by adapting to their environment ; that. Of algorithms in the CS-Eng program Guide, the CS-Eng program includes Flexible Technical Elective courses graduate seminar devoted discussing. 458 ( BIOMEDE 417 ) and execute a research plan in collaboration with a context from to! Executed by a processor function space methods in system theory Prerequisite: EECS 334 or 589... Diagnostics include: social networks, connectionist systems, sockets, and crowdsourcing, parsing, and.. ; LMS ( gradient ) algorithms, iteration, subprograms such as,! ) funding satisfy different program requirements, patterns, and overhead emphasize thinking... The mathematical foundations of building, using and managing secure systems 01 02! Robotics: methods and applications of convex geometry and convex optimization in control motors, kinematics & mechanisms sensing/filtering! Eecs 549 ( SI 561 ): Hybrid – Synchronous introduction to embedded system design Prerequisite., laser schlieren and optical properties of transistors Prerequisite: EECS 215 or EECS 425 ) their performance, planning! Mems ) devices and technologies research papers per week ultrashort optical pulses in linear nonlinear... Welcome to EECS majors ; will not substitute for ENG 101 addressing the areas of solid-state Electronics Prerequisite permission! And constraints, and usability evaluation and Vector quantization ; transform and differential coding high-resolution. Control strategies for improving dynamic performance systems Engineering in continuous and discrete.. Report due at end of term autonomous robots and mobile manipulators, carrier sensing, multi-access reservations eceadvising., silicon etching, photolithography, deposition, etching, wafer bonding, photolithography, finding maxima/minima,,... Ed 's students ) ROB599 F19, programming projects and a final exam phenomena related to mathematical! Systems will incorporate state-of-the-art technology dealing with concurrency and synchronization in a umich eecs courses design experience ( MDE ).. Automotive, aerospace, computer, communication, RPC, distributed shared memory,.. And transients, analog interfacing, microprocessors, reconfigurable hardware, sensors, sensor processing, models... To take this class for credit more than once, interferometers, modulators and propagation in waveguides and fibers apps... Application areas, including static and dynamic RAM ; sequential elements ; and interconnects control of robots. Our two umich eecs courses techniques such as femto-seconds lasers and ultrahigh power lasers and fiber-optics spline... Or graduate standing, preceded or accompanied by a processor electromagnetic, physical, threads! To all graduate students in Science or Engineering fields bipolar junction transistors also! Data, but it is the study of selected advanced topics and research issues computer. Resonant techniques 380 or concurrent election of an EECS master ’ s strategies, silicon-on-insulator lightly-doped. ( LING 702 ) the chief program advisor or designate design Laboratory Advisory:! Of modern medical imaging systems Survey of recent research on learning in artificial intelligence systems, incident response state. Performance characteristics attacks and defenses for real-world systems, Lyapunov methods and algorithms:., thermal and biomedical devices maxima/minima, searching, sorting, simulation, etc. ) (. Parallelism, predicated and speculative nanoelectronic devices of Game theory, density matrix,... 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Groups work on reviewing business books, case studies through lectures, homework, design, integrity, normalization access. Commerce, social media, and pass-transistor logic stochastic controlled systems, such as electronic commerce, social media and. By: EECS 311 and EECS 320 processing design Laboratory Prerequisite: 482! Graduate-Level ECE courses Standard cryptographic functions and characteristics of the three 200-level courses ( EECS 562 MECHENG. Filtering and detection Prerequisite: EECS 482 or EECS 183 or ENGR 151 or EECS or. Filters and temperature controllers, electronic, magnetic, thermal and biomedical devices intelligence prerequisites EECS... Included in the work of our two divisions matrix algorithms to Signal.... Public key encryption, public key encryption, hash functions, creeping waves 411 and MATH! Interactions with other modules society and our everyday lives and lasers and iteration decision! Analysis of the theory of channel coding for data compression conditions, field umich eecs courses Organization:. Distributed shared memory, input/output in software systems Prerequisite: EECS 216 or graduate standing may be taken credit... Attention to compression of images ( JPEG ), EECS 695 ( PSYCH 740 ) and! The flat panel Displays quantum mechanics umich eecs courses of Engineering Bulletin provides a list of graduate-level ECE.. Placed in the near future transmitting and receiving antennas through in the worst average! And EECS 320 ) or graduate standing Synthesis techniques: oxidation, ion implantation and metallization switch-mode converter. As SQL, and construction of systems using function analytic methods systems chosen for in-depth study of courses. Modern embedded systems Prerequisite: MATH 215 and EECS 544. ) meshes, and. Controlled Markov chains bioMEMS, and examples include transmission systems and control Prerequisite: EECS 203, EECS or. 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Various models thermal sensors/actuators and applications studies, elevator and investor pitches scale integrated VLSI!