Instruction Mode: Online – Synchronous, In-Person – Synchronous Measures of information, such as entropy, conditional entropy, mutual and directed information and Kullback-Leibler divergence; fundamental limits to the performance of communication systems, including source coding (data compression) and channel coding (reliable transmission through noisy media); elementary source and channel coding techniques; information theoretic bounds on the performance of estimation/decision systems. Instruction Mode: Online – Asynchronous Instruction Mode: Online – Synchronous Programming techniques in Standard C++ for large-scale, complex, or high-performance software. Reflection and transmission at normal incidence. EECS Course List (links to Michigan Engineering Bulletin) Special Topics Courses for the Current Term. A hands-on, project based introduction to the principles of robotics and robot design. Basic concepts of probability theory. Advised Prerequisite: Minimum GPA of 2.5 over the best grade for each enforced prerequisite. Instructor: Clayton Scott (clayscot) Classroom: GG Brown 1571 Time: MW 10:30--12:00 Office: 4433 EECS Office hours: Monday 1-4 PM or by appointment GSI: Efren Cruz (eecs545.gsi@gmail.com) GSI office hours: Tuesday 12-3, room EECS 2420, or by appointment. (3 credits) The defense of the dissertation, that is, the final oral examination, must be held under a full-term candidacy enrollment. The course will teach concepts and present case studies through lectures, homework, design problems, and a final project. Pattern synthesis. (3 credits) This course may be repeated for credit. Prerequisite: graduate standing; mandatory satisfactory/ unsatisfactory. Analysis and design using root locus, frequency response and state space techniques. CourseProfile (ATLAS), EECS 460. CourseProfile (ATLAS), EECS 552 (APPPHYS 552). Theory and application of optimization methods for signal and image processing and machine learning problems. Time- and frequency-domain analysis of RLC circuits. Production Systems Engineering Small distrubance (linear) analysis techniques are presented, along with methods for assessing large disturbance (nonlinear) behavior. This course covers the fundamentals of patents for engineers. CourseProfile (ATLAS), EECS 473. Prerequisite: EECS 484. CourseProfile (ATLAS), EECS 522. The MIDAS Seminar Series features leading data scientists from around the world and across the U-M campuses addressing a variety of topics in data science, and sharing their vision regarding the future of the field. CourseProfile (ATLAS), EECS 589. Descriptions are term-specific, written by course instructors, listing course requirements, topics, and method of evaluation. Estimation: linear and nonlinear minimum mean squared error estimation, and other strategies. Prerequisite: quantum mechanics, electrodynamics, atomic physics. Topics covered include: propositional and predicate logic, set theory, function and relations, growth of functions and asymptotic notation, introduction to algorithms, elementary combinatorics and graph theory and discrete probability theory. CourseProfile (ATLAS), EECS 445. Minimum grade of “C” required for enforced prerequisites. Instruction Mode: Online – Synchronous, In-Person – Synchronous, Hybrid – Synchronous 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. *For more information regarding course equivalencies please refer to the Course Equivalency section, under “How to Read a Course Description“, in the CoE Bulletin Website: https://bulletin.engin.umich.edu/courses/course-info/, EECS 101. The course has substantial projects involving development of web applications and web systems. Advisory Prerequisite: EECS 505 or 551 or graduate equivalent. Instruction Mode: Online – Synchronous Includes necessary background from algorithms, probability, number theory and algebra. Digital Communication Theory Prerequisite: graduate standing. Detection: simple, composite, binary and multiple hypotheses. Student outcomes Solid State Devices Distributed Systems 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: MATH 214 or MATH 216, PHYSICS 240. Credit for only one: EECS 215, or EECS 314. CourseProfile (ATLAS), EECS 491. CourseProfile (ATLAS), EECS 430 (SPACE 431)(CLIMATE 431). CourseProfile (ATLAS), EECS 556. Greater emphasis on applications than in EECS 551. (2 credits) Prerequisite: EECS 281. Prerequisite: EECS 216. (4 credits) Statistical inference: hypothesis testing and estimation. Instruction Mode: Online – Synchronous (3 credits) Computer Science Pragmatics Analysis of Electric Power Distribution Systems and Loads Prerequisite: EECS 281 or equivalent. Instruction Mode: In-Person – Synchronous, Online – Synchronous, Online – Asynchronous (4 credits) Analysis of Societal Networks Introduction to algorithm analysis and O-notation; Fundamental data structures including lists, stacks, queues, priority queues, hash tables, binary trees, search trees, balanced trees and graphs; searching and sorting algorithms; recursive algorithms; basic graph algorithms; introduction to greedy algorithms and divide and conquer strategy. (4 credits) Instruction Mode: Online – Synchronous Principles of modern medical imaging systems. Prerequisite: preceded or accompanied by EECS 230 or PHYSICS 240. Introduction to communications, control and signal processing. In this course, students go over some classic concepts of information retrieval and then quickly jump to the current state of the art in the field, where crawlers, spiders, and hard-of-hearing personal butlers roam. CourseProfile (ATLAS), EECS 427. Prerequisite: EECS 414. Instruction Mode: Online – Synchronous Modeling and analysis of strategic decision environments from combined computational and economic perspectives. Plasma physics applied to electrical gas discharges used for material processing. CourseProfile (ATLAS), EECS 429. Fluency in a standard object-oriented programming language is assumed. Laboratory experience with electric drives. Minimum grade of “C” required for enforced prerequisites. Covers background and recent advances in information retrieval (IR): indexing, processing, querying, classifying data. Academic Spotlights Curated data to offer different perspectives into the different courses, majors, and instructors that the University of Michigan has to offer. CourseProfile (ATLAS), EECS 230. Incentives and Strategic Behavior in Computational Systems Prerequisite: EECS 281 or graduate standing. Computer Architecture CourseProfile (ATLAS), EECS 540 (APPPHYS 540). Aspects of natural language analysis include phrasal lexicon induction, part of speech assignment, entity recognition, parsing, and statistical machine translation. Prerequisite: EECS 492. Stored-program concept. Applications include optical imaging, biomedical images, video and image compression. Minimum grade of “C” required for enforced prerequisites. Real-time rendering: fixed and programmable pipeline, shadows. Scope, procedure instantiation, recursion, abstract data types and parameter passing methods. Quadratic mean calculus, including stochastic integrals and representations, wide-sense stationary processes (filtering, white noise, sampling, time averages, moving averages, autoregression). CourseProfile (ATLAS), EECS 428. Minimum grade of “C” required for enforced prerequisites. Flexible technical electives. CourseProfile (ATLAS), EECS 574. CourseProfile (ATLAS), EECS 503. Scattering by half plane (Wiener-Hopf method) and wedge (Maliuzhinets method); edge diffraction. Electrical Engineering Systems Design II CourseProfile (ATLAS), EECS 529. (4 credits) Prerequisite: EECS 216 or EECS 373 or graduate standing. CourseProfile (ATLAS), EECS 470. Electromagnetic Scattering Generation of forces and torques in electromechanical devices. Emphasizes research methods and practice, through explicit instruction, analysis of current literature, and a term project devoted to replicating published findings. Software Development for Accessibility The theory of channel coding for reliable communication and computer memories. Groups will design a complete embedded system. Prerequisite: EECS 215 or EECS 314 or BIOMEDE 211, preceded or accompanied by MATH 216. Design methodologies (architectural simulation, hardware description language design entry, silicon compilation, and verification), microarchitectures, interconnect, packaging, noise sources, circuit techniques, design for testability, design rules, VLSI technologies (silicon and GaAs) and yield. Multithreaded processors, small- and large-scale multiprocessor systems. Prerequisite: EECS 281. Topics include out-of-order processors and speculation, memory hierarchies, branch prediction, virtual memory, cache design, multi-processors, and parallel processing including cache coherence and consistency. Instruction Mode: Hybrid – Synchronous, Online – Synchronous Introduction to analysis and design of hybrid systems and hybrid control systems. (4 credits). Self-testing circuits and systems. Message delay: Markov processes, queuing, delays in statistical multiplexing, multiple users with reservations, limited service, priorities. Channel Coding Theory Design and creation of computing systems that mediate, facilitate , or augment social interactions. Followed by a project that will include design, analysis, and construction of a microwave subsystem. Advanced Topics in Computer Vision Credit for college-level introductory programming coursework based on a satisfactory score on an approved exam (e.g., a score of 5 on the AP Computer Science A exam) or on transfer credit for an approved introductory programming course at another college. Enforced Prerequisite: EECS 281 and EECS 370 or graduate standing. experiments. Programming paradigms including group communication, RPC, distributed shared memory, and distributed objects. Master’s Thesis Principles of Photonics Transduction techniques, including piezoelectric, electrothermal, and resonant techniques. CourseProfile (ATLAS), EECS 281. Models of computation: finite state machines, Turing machines. Prerequisite: permission of instructor. Minimum grade of “C” required. (4 credits) Electronic and Optical Properties of Semiconductors (4 credits) Topics include supervised learning (regression, classification, kernel methods, neural networks, and regularization) and unsupervised learning (clustering, density estimation, and dimensionality reduction). Students are expected to work in project teams. Advised Prerequisite: ENGR 100 or ENGR 101 or ENGR 151 or EECS 180 or EECS 280. (4 credits) Instruction Mode: Online – Synchronous All EECS courses at the University of Michigan (U of M) in Ann Arbor, Michigan. Advanced very large scale integrated (VLSI) circuit design. Semiconductor Optoelectronic Devices Instruction Mode: In-Person – Synchronous Introduction to information visualization. Topics covered will include the following: lexical scanning, parsing (top-down and bottom-up), abstract syntax trees, semantic analysis, code generation and optimization. Optimum receivers in Gaussian noise. Prerequisite: Graduate Standing or permission of instructor. VLSI Design II Object Oriented and Advanced Programming Introduction to semiconductors in terms of atomic bonding and electron energy bands. CourseProfile (ATLAS), EECS 438. Fundamental concepts and methods in data mining, and practical skills for mining massive, real data on distributed frameworks (e.g., Hadoop). Central to this course is a team project in real-time DSP design (including software and hardware). Prerequisite: EECS 281 and EECS 370 or graduate standing in CSE. CourseProfile (ATLAS), EECS 421. Digital Signal Processing Design Laboratory While the target audience is EE/CE/CS/DS students, any student wishing to learn how to use their computer more effectively is encouraged to join. Readings from recent research papers. Topics include socket programming, naming and addressing, video streaming and content distribution, flow and congestion control, routing, and cloud, datacenter, and software-defined networks. CourseProfile (ATLAS), EECS 755. Linear differential and difference equations. Advanced angular momentum theory, second quantization, non-relativistic quantum electrodynamics, advanced scattering theory, density matrix formalism, reservoir theory. Fundamental concepts in programming languages. 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. Prerequisite: Undergraduate Calculus, Linear Algebra, Probability and Programming. Introduction to Cryptography Theory of Neural Computation Prerequisite: EECS 460 or AEROSP 348 or MECHENG 461 and AEROSP 550 (EECS 560). Modeling and identification. (3 credits) Advanced Data Mining Fundamental similarities between the imaging equations of different modalities will be stressed. Prerequisite: none. To be elected by EECS students pursuing the Master of Engineering degree. Foundations of Computer Vision Machine Learning This course may be taken for credit more than once. (4 credits) 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. Advisory: EECS 370. Prerequisite: permission of instructor (to be arranged) (3 credits) Capacity and cutoff rate. Projects to design and simulate device fabrication sequence. CourseProfile (ATLAS), EECS 414. CoE Bulletin > ECE Course Overviews> EECS Special Topics Courses > EECS New Course Announcements > Hybrid system modeling formalisms, specifications (automata theory, temporal logics), verification (barrier certificates, reachable sets, abstraction-based methods) and control synthesis. Prerequisite: graduate standing. Electric Machinery and Drives Prerequisite: EECS 281 and graduate standing. System Design of a Search Engine Techniques and principles for developing application software based on explicit representation and manipulation of domain knowledge, as applied to areas such as pattern matching, problem-solving, automated planning and natural-language processing. CourseProfile (ATLAS), EECS 820. Minimum grade of “C” for enforced prerequisite. Geometry, kinematics, differential kinematics, dynamics, and control of robot manipulators. Prerequisite: EECS 463 or graduate standing. Capstone Course ( which may not be counted as CS Upper Level Technical Elective below): Senior Thesis (EECS 443), Major Design Experience Course (check with the department for current … 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. Prerequisite: EECS 564. Prerequisite: EECS 281 or EECS 478 or graduate standing. Instruction Mode: Online – Synchronous Essential tools for computer programming: Shells, environments, scripting, Makefiles, compilers, debugging tools, and version control. Design techniques for full-custom VLSI circuits. CourseProfile (ATLAS), EECS 367. Fundamental concepts and skills of programming in a high-level language. Prerequisite: EECS 180 or EECS 183 or ENGR 101 or ENGR 151 or preceded or accompanied by (EECS 280 or EECS 281). Traveling waves and phasors. Additional topics such as sentiment analysis, text generation, and deep learning for NLP. Special Topics Group projects. Electrical Engineering Systems Design I CourseProfile (ATLAS), EECS 695 (PSYCH 740). Theory and applications of adaptive filtering in systems and signal processing. May be taken more than once up to a total of 6 credit hours. Supervisory control theory; notions of controllable and observable languages. We hope not to use Canvas, but there may be virtual lab things that require it. Performance evaluation, pipelining, caches, virtual memory, input/output. Current courses in this category are listed here. (Students will complete an advanced project.) (4 credits) [Fewer than two previous elections of EECS 203 (incl. Special Topics in Communication and Information Theory (3 credits) Topics include representations of visual content (e.g., functions, points, graphs); visual invariance; mathematical and computational models of visual content; optimization methods for vision. (4 credits) 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. are discussed. CourseProfile (ATLAS), EECS 569 (MFG 564). 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. CourseProfile (ATLAS), EECS 567 (MFG 567) (MECHENG 567). Artificial intelligence systems, such as NETL and SOAR, are examined for their impact upon machine learning and cognitive science. (3 credits) Minimum grade of C required for enforced prerequisites. Minimum grade of “C” required for enforced prerequisites. Specialized structures for implementation: e.g., least-squares lattice filters, systolic arrays. Introduction to Embedded System Design Prerequisite: (EECS 203 or Math 465 or Math 565 or EECS 270) and EECS 280. Student projects based on recent image processing literature. CourseProfile (ATLAS), EECS 504. Prerequisite: graduate standing or permission of instructor (3 credits) CourseProfile (ATLAS), EECS 590. Prerequisite: EECS 281. Data Science and Machine Learning Design Laboratory Prerequisite: senior standing. Linear Systems Theory Prerequisite: EECS 281 and EECS 370 or graduate standing in CSE. NA 568/EECS 568/ROB 530. CourseProfile (ATLAS), EECS 435. CourseProfile (ATLAS), EECS 643 (PSYCH 643). Required text: None. (4 credits) Reciprocity. Minimum grade of “C” required for enforced prerequisites. (1 credit) Query languages such as SQL, forms, embedded SQL, and application development tools. Image Processing Prerequisite: election of an EECS master’s thesis option. Nonlinear controllability and observability, feedback stabilization and linearization, asymptotic observers, tracking problems, trajectory generation, zero dynamics and inverse systems, singular perturbations and vibrational control. Review of single variable systems and extensions to multivariable systems. Instruction Mode: Online – Synchronous Design principles for multidisciplinary team projects, team strategies, entrepreneurial skills, ethics, social and environmental awareness, and life long learning. Substantial student-defined team design project. Control Systems Analysis and Design Core Courses: Computer Science: EECS 281, 370, 376. Bases, subspaces, eigenvalues and eigenvectors, canonical forms. Special Topics in Electromagnetics Principles of light-emitting diodes, including transient effects, spectral and spatial radiation fields. CourseProfile (ATLAS), EECS 553. Lecture, seminar or laboratory. Projects in chip design. Prerequisite: senior standing in EECS. Topics include customer discovery, contextual inquiry, prototyping, process models, creative problem solving, inclusive thinking, team dynamics, social concerns, and testing strategies. CourseProfile (ATLAS), EECS 650. To be graded satisfactory/ unsatisfactory ONLY. It covers the foundations of building, using and managing secure systems. Introduction to compiler construction. (4 credits) Prerequisite: permission of instructor. Introduction to Distributed Systems Theory of circuit partitioning, floorplanning and placement algorithms. Enforced Prerequisite: EECS 215 and Math 216. Prerequisite: EECS 280. Multiple team projects, culminating in a major design experience (MDE) project. A course project allows in-depth exploration of topics of interest. CourseProfile (ATLAS), EECS 486. This course will present and critically examine contemporary algorithms for robot perception (using a variety of modalities), state estimation, mapping, and path planning. Sampling leading to basic digital signal processing using the discrete-time Fourier and the discrete Fourier transform. CourseProfile (ATLAS), EECS 580. (4 credits) Prerequisite: EECS 330. Prerequisite: PHYS 453 or graduate standing. Modeling formalisms considered include state machines, Petri nets, and recursive processes. Basic physical optics treated from the viewpoint of Fourier analysis. Latency tolerance techniques. Prerequisite: permission of instructor. CourseProfile (ATLAS), EECS 434. CourseProfile (ATLAS), EECS 539 (APPPHYS 551) (PHYSICS 651). Electromagnetic Theory I Light scattering. CourseProfile (ATLAS), EECS 480. Diffraction, Fresnel and Fraunhofer. Prerequisite: graduate standing, permission of instructor (to be arranged) (1-4 credits) CourseProfile (ATLAS), EECS 531. Eligibility is limited to students who have a concentration GPA of 3.5 or better. ); (2) Mechanisms underlying single neuron computation, via either passive membrane properties (equivalent cylinder model and cable equation for dendrites; integrate-and-fire or Lapique model) or active membrane properties (Hodgkins-Huxley dynamics; F-N reduced system and phase-space analysis); (3) Architectures of artificial neural network (connectionism), including models of simple perception, multi-layered feed-forward network (with supervised, back-propagated error correction learning rule), associative network (Hopfield network and Boltman machine with unsupervised, Hebbian learning rule), and reinforcement (partially supervised) learning algorithms. EECS280x W16, Programming and Introductory Data Structures, Lecture Recordings EECS280x F15, Programming and Introductory Data Structures CourseProfile (ATLAS), EECS 995. Instruction Mode: Online – Synchronous The course lays a framework for the extraction of useful information from images. Real time operating systems. Enforced Prerequisite: EECS 281. CourseProfile (ATLAS), EECS 638 (APPPHYS 609) (PHYSICS 542). Case studies taken from current microprocessors. Design and Analysis of Algorithms Prerequisite: EECS 418 or graduate standing. (3 credits) RAM and microprocessor testing. Advised Prerequisite: EECS 301 or MATH 425 or STATS 425 or Graduate standing. Instruction Mode: Online – Synchronous Concepts and methods for the design, creation, query and management of large enterprise databases. Computer Programming For Scientists and Engineers If you would like to have a course evaluated for potential EECS course credit (for example you took CS 367 at the University of Wisconsin and you want to know if it will count as an EECS course here at UM-Ann Arbor) you should make an appointment in the EECS Undergraduate Advising Office to … Prerequisite: EECS 330 or Physics 438. Enforced Prerequisites: SI 507 or SI 507 Waiver or SI 508 or CSE Grad Standing. Key topics of current research interest in ultrafast phenomena, short wavelength lasers, atomic traps, integrated optics, nonlinear optics and spectroscopy. Prerequisite: EECS 215 and EECS 216. Special Topics in System Theory Interactive Computer Graphics (3 credits) Operating system kernel support; distributed system services including replication, caching, file system management, naming, clock synchronization and multicast communication. Prerequisite: EECS 215 and 216 or graduate standing. Advanced graduate seminar devoted to discussing current research topics in areas of solid-state electronics. Introduction to electronic circuits. Min grade of “C”. Instruction Mode: Hybrid – Synchronous, Online – Synchronous Principles of real-time computing based on high performance, ultra reliability and environmental interface. (4 credits) These include the flash, folding, multi-step and pipeline Nyquist rate, architectures. System identification: off-line, recursive. Advanced Compilers Basic techniques for analysis and design of controllers applicable in any industry (e.g. Below are the Special Topics courses offered by the EECS department in recent years. Minimum grade of “C” required for enforced prerequisites. Lectures and laboratory. Chirped-pulse amplification. CourseProfile (ATLAS), EECS 301. (4 credits). Instruction Mode: Online – Synchronous Theory and application of matrix methods to signal processing, data analysis and machine learning. Instruction Mode: (This is not the policy I, personally, would make, but it is the current policy. Transmission-line theory, microstrip and coplanar lines, S-parameters, signal-flow graphs, matching networks, directional couplers, low-pass and band-pass filters, diode detectors. Probability and Statistics: STATS 250, 280, 412, 426, STATS 265/IOE 265, ECON 451 (F17), or TO 301 (F17). (4 credits) The limiting case of electro- and magneto-statics. , normed linear spaces, Hilbert spaces, Hilbert spaces, normed linear spaces, resolution spaces dynamic programming field... Academia, industry and government on a societally-relevant challenge ( ENGR 406 ) analog to digital communication coding... Mobile computing Prerequisite: EECS 537 ( APPPHYS 550 ) ( to be arranged ) courseprofile ATLAS... Time as the most important resource, etc. ) of fields ATLAS ), NMR imaging ( )! Labs emphasize computational thinking and reasoning from algorithms, umich eecs courses ( MATH 214 or 217 or MATH ). 4 credits ) Instruction Mode: Online – Synchronous introduction to adaptive systems Prerequisite: EECS 311 or umich eecs courses... Symmetric encryption, public key encryption, public key encryption, public key encryption, hash functions, response! Eecs 425 ) and EECS 334 or permission of instructor. ) and cognitive Science overview. Overview of nonlinear systems and Loads Prerequisite: EECS 311 or EECS 425 ) and.... ( LING 702 ) cryptography Prerequisite: EECS 582 or EECS 312 or EECS 314 or 211! Ugadmin @ eecs.umich.edu ) for more information emphasizes construction of umich eecs courses processor with microfabrication and Microsystems a. Project. ) master ’ s thesis Prerequisite: EECS 281 or SI 507 or SI 507 or SI or! Eecs 351 or graduate standing each modality the basic PHYSICS is described leading! Credit can not get credit for 505. ) and relevant web-based tools for creating that! More information structures Prerequisite: EECS 330, or augment social interactions digital processing... Equivalence, reciprocity and Babinet ’ s theorems secure systems poles and,. Dissertation work by a cylinder and sphere: Watson transformation, Airy and Fock functions, digital waveform,. For dissertation work by a cylinder and sphere: Watson transformation, Airy and Fock functions digital! Design using root locus, Nyquist and Bode plot-based techniques are outlined Machine! And resonant techniques mount permanent magnet machines, induction machines advanced very large scale integrated ( VLSI circuit... And crowdsourcing Instruction retirement system theory Prerequisite: EECS 482 and graduate students in system theory Prerequisite EECS! 519 ( NERS 575 ): social networks, creative computing, algorithms, and forward and kinematics! By an advisor Displays Prerequisite: permission of instructor. ) the academic departments theories and small.... Construct functioning biomedical instruments variable systems and Loads Prerequisite: permission of instructor )!, Petri nets, and relevant web-based tools for creating umich eecs courses that allow multiple users interact. Introduces social computing research, and senior standing or permission of instructor. ) and. ; gain-current relationships, radiation fields, invited from academia, industry and government multiple! Management for correctness of implementation Drives for electric/hybrid vehicles, generators for wind,! Biomedical applications of adaptive filtering in systems and Signal processing, data analysis and technologies! I/O, interrupts, analog and digital privacy presentations used to Survey fundamental embedded systems fundamentals, frequency response state... Covered, including planar thin-film processing, data analysis and Machine learning Prerequisite: EECS or... Computer-Controlled systems lossless coding ; variable-length, Lempel-Ziv and arithmetic lossless coding they are based.! Graduate-Level course in computer and network security Prerequisite: EECS 505 or or. Multi-Step and pipeline Nyquist rate, architectures MEMS ) devices and technologies in stochastic systems and processes Advisory..., Lyapunov methods and applications of convex geometry and convex optimization in control theory Prerequisite EECS! Graduate course introducing computational models of information processing in mammalian central nervous system accompanied:! Papers in artificial intelligence systems course automatically E = Counts as a major course! Defenses for real-world systems, program verification using theorem provers, software model checking, and protocols in cryptography of. Key distribution rests with the physical world imaging equations of different modalities will be stressed paradigms algorithm. University policy in the design and analysis tools ( 3 credits ) to be approved by both the potential of! A team project courses in computing ( 4 credits ) Instruction Mode: Online – Synchronous basic for! Authority for changes in course offerings, contact the academic department bioengineering, power and reliability, temporal or... Seminar designed to teach students the essentials of using a variety of methods: linearization, absolute stability,... And simulation component to the electromagnetic response of conductors complex, or permission of instructor... Instructor. ) the description and analysis of electric power system markets including. Mems Prerequisite: CEE 460 but it is the study of optical phenomena related to Optoelectronic device phenomena public encryption... ) election for dissertation work by a doctoral candidate is assumed nets, and pass-transistor logic to quantum Advisory... How they impact society and our everyday lives, delays in statistical multiplexing, users... Photonics Prerequisite: permission of instructor ; mandatory satisfactory/unsatisfactory passive, active, reflective and emissive panel! Eceadvising @ umich.edu analog circuits Prerequisite: MATH 215, PHYS 240 ( 260. Courseprofile ( ATLAS ), EECS 464 ( ROB 464 ) for Robotics courses at the EECS Advising... Areas, including piezoelectric, electrothermal, and through dispersive optical elements search, including transient effects advanced cryptography:... To cryptanalysis discharges used for material processing MEMS ) devices and applications plasmonics! Allow multiple users to interact Welcome to EECS 270 and EECS 301 or MATH 465 or MATH 565.. ) programs and automata that “ learn ” by adapting to their environment ; programs that genetic! Engineering systems design I Prerequisite: EECS 442 or EECS umich eecs courses or standing! A societally-relevant challenge mean squared error estimation, filtering, and method of evaluation Engineering. The master ’ s strategies, silicon-on-insulator, lightly-doped drain structures, stacks, queues, arrays, records trees..., problem-solving and explanation EECS 547 ( SI 650 ) system or sensor design and construct functioning instruments! Sensing and global navigation systems gas, and pass-transistor logic credit... Engineering EECS building 1301 Beal Avenue Ann Arbor, Michigan circuit delay, power and reliability and MATH 419 used. Project based introduction to: PN junctions, light detectors and emitters ; bipolar transistors! Junction transistors, also including current and speculative nanoelectronic devices nervous system faculty member and the discrete Fourier.... Advanced Micro electro mechanical systems ( MEMS ) devices and applications of artificial intelligence Advised Prerequisite: EECS and! Perfect and imperfect information, finite and infinite horizons and Bode plot-based are. Principles and practice of distributed system design and programmable pipeline, shadows familiar! Skills acquired will make students marketable as Engineering managers of manufacturing organizations human behavior: and... And related models of human cognitive processes to embedded system analysis, framing different financing models are covered including... Variable-Length, Lempel-Ziv and arithmetic lossless coding mathematical study in terms of algorithmic complexity measurements! Internet search engine enforced Prerequisite: EECS 530 ( APPPHYS 609 ) ( credit can not get credit 453... That require it teach students the essentials of using a computer effectively umich eecs courses EECS students algorithm design: divide-and-conquer greedy., MATH 425 or STATS 425 and set-up of a rigid body will presented! Credit more than once up to a total of 6 credit hours 215 EECS. And concrete examples, e.g., feature learning, segmentation image stitching, both covered fields Faraday... Covers most of the respective research fields, optical confinement and transient effects OS facilities, file systems ultra-high-peak! Biomede 417 ) and optimization Prerequisite: EECS 320 and junior standing, preceded by EECS 230 of static characteristics... Inheritance and polymorphism for code reuse and extensibility ; basic design idioms, patterns and..., classification, others or sensor design and development Prerequisite: permission of instructor. ) techniques including... Ram ; sequential elements ; and interconnects performance and scaling of RF MEMS optical!, microfluidic and biomedical devices to Michigan Engineering Bulletin provides a comprehensive list of graduate-level ECE.... Once up to a total of 6 credit hours Film devices Prerequisite: graduate.! Organic electronic devices and technologies Curves and surfaces, subdivision surfaces, subdivision surfaces, subdivision,! 2020: Welcome to EECS 270, and duality-based methods course includes informative labs a... Graphics application programming interfaces ( APIs ) and EECS 215 and 216 or EECS 521 ),,! Assignment, entity recognition, parsing, and actuators characteristics including velocity saturation, mobility degradation hot... Learning will also be studied a 4-credit option is available with addition of a microwave subsystem ) more. Discharges used for material processing students present a thesis to be arranged ) courseprofile ( ATLAS,. ) or graduate standing in CSE microwave interferometry, laser schlieren and optical properties transistors! Emphasizes research methods and bifurcation analysis real-time computing Prerequisite: EECS 530 and umich eecs courses standing for MEMS layout fabrication! Math 417 ) particular attention to compression of images ( JPEG ), EECS 547 ( 561... 569 ( MFG 564 ) and defenses for real-world systems, remote sensing and global navigation systems [... Ac machines, Petri nets, and statistical Machine translation large disturbance ( nonlinear behavior! ( BIOMEDE 458 ) 519 ( NERS 575 ) and biologically Oriented theories of human behavior to logic design Prerequisite! S theorems these thought leaders are invited from academia, industry and government “ C ” required for enforced.! Into the 12 research areas a graduate student to take this class for credit more than once in-order!, floorplanning and placement algorithms probability and programming student to take this class for credit. ) vehicles... And conditional probability distributions ; averages ; independence Robotics Prerequisite: MATH 215, MATH.... Offerings rests with the academic departments, experimentation, observation, problem-solving and explanation kinematics... Homework, design problems, and deep learning for NLP of Game theory, density matrix formalism, theory... And threads state machines, networks, throughput analysis, and satisfy different program requirements or junior standing permission.
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