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. Natural Language Processing VLSI Design I These thought leaders are invited from academia, industry and government. (4 credits). (to be arranged) (1-4 credits) Instruction Mode: Online – Synchronous Emphasis is given to development of large, complex software systems. Prerequisite: EECS 281 and EECS 376 Minimum grade of “C” required for enforced prerequisites. Minimum grade of “C”. Instruction Mode: In-Person – Synchronous CourseProfile (ATLAS), EECS 553. (1 credit) Time- and frequency-domain analysis of RLC circuits. Data Science and Machine Learning Design Laboratory Applications include signal denoising, compressed sensing, matrix completion, robust regression, and classifier design. (3 credits) Program language syntax and static and runtime semantics. Theory: motors, kinematics & mechanisms, sensing/filtering, planning, pinhole cameras. Security Engineering by Ross Anderson Cryptography Engineering by Ferguson, Schneier, and Kohno : Resources: Security Research at Michigan Security Reading Group (SECRIT) EECS 588 (graduate-level security class) : Prerequisites: EECS 281 required; EECS 201 and EECS 370 recommended Calendar: The course calendar is displayed below. System architectures. Students are expected to work in project teams. CourseProfile (ATLAS), EECS 582. 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: EECS 320 or graduate standing. Prerequisite: senior standing in EECS. Renewal and regenerative processes, Markov chains, random walk and run, branching processes, Markov jump processes, uniformization, reversibility and queuing applications. Instruction Mode: The College of Engineering Bulletin provides a comprehensive list of courses offered at the CoE level. Course Mechanics > – requires umich.edu email account. Individual study of selected advanced topics in electrical engineering and computer science. (4 credits) (3 credits) See lists alphabetically and numerically. Theoretical analysis of the chemistry and physics of process technologies used in micro-electronics fabrication. CourseProfile (ATLAS), EECS 334. Mathematical representations: state equations, transfer functions, impulse response, matrix fraction and polynomial descriptions. Radio frequency and wireless communication. Instruction Mode: Online – Synchronous Concepts and techniques for designing computer system user interfaces to be easy to learn and use, with an introduction to their implementation. Current topics of interest in computer architecture. CourseProfile (ATLAS), EECS 498. (4 credits) Topics include: semiconductor growth, material characterization, lithography tools, photo-resist models, thin film deposition, chemical etching, plasma etching, electrical contact formation, micro-structure processing and process modeling. CourseProfile (ATLAS), EECS 414. Minimum grade of “C” required for enforced prerequisites. CourseProfile (ATLAS), EECS 670. Applications: filtering, denoising, deconvolution, classification, others. 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). Fundamental concepts and methods in data mining, and practical skills for mining massive, real data on distributed frameworks (e.g., Hadoop). Analysis of Societal Networks Topics include location and context awareness, mobile data access, resource management, consistency protocols, mobile and ad hoc networking, networked sensors, security and privacy. Social Computing Systems Research Work in Electrical Engineering and Computer Science CourseProfile (ATLAS), EECS 440. Optimization of systems described by Markov processes; dynamic programming under perfect and imperfect information, finite and infinite horizons. CourseProfile (ATLAS), EECS 519 (NERS 575). Reflection and transmission at normal incidence. DC/DC converter design for PCBs. Drive, snubber circuits. Instruction Mode: Online – Synchronous Instruction Mode: Analysis of micromachined capacitive, piezoresistive and thermal sensors/actuators and applications. (4 credits) [(EECS 203 or MATH 465 or 565) and EECS 280; (C or better, NO OP/F)] and [Fewer than two previous elections of EECS 281 (incl. Exam/Transfer Introductory Computer Programming Credit CourseProfile (ATLAS), EECS 583. Prerequisite: permission of instructor. Instruction Mode: Online – Synchronous Introduction to Quantum Nanotechnology Scattering by half plane (Wiener-Hopf method) and wedge (Maliuzhinets method); edge diffraction. Students must have taken EECS 203 and EECS 280 or have an equivalent background. experiments. Prerequisite: Senior standing, EECS 281, and at least four credit hours of Upper Level Electives from list in either Computer Science or Computer Engineering. Graduate Foundations of Data Structures and Algorithms Click Here. Prerequisite: (EECS 215 and EECS 216 and preceded or accompanied by EECS 320) or graduate standing. Prerequisite: MATH 215 and MATH 216 and PHYSICS 240 or graduate standing. CourseProfile (ATLAS), EECS 435. Prerequisite: graduate standing. Task analysis, design of functionality, display and interaction design, and usability evaluation. Quality of services and energy management for correctness of implementation. Topics include search, logic, knowledge representation, reasoning planning, decision making under uncertainty, and machine learning.` CourseProfile (ATLAS), EECS 594. Model-predictive control of hybrid systems. CourseProfile (ATLAS), EECS 311. computational complexity emphasizing NP-hardness. (2 credits) All of these courses are geared toward different audiences, have different prerequisites, and satisfy different program requirements. Instruction Mode: Online – Synchronous CourseProfile (ATLAS), EECS 521. Transduction techniques, including piezoelectric, electrothermal, and resonant techniques. out-of-order, multi-core, SMT) processor using an HDL. Prerequisite: permission of instructor or graduate standing. Instruction Mode: Hybrid – Synchronous/Asynchronous, Online – Synchronous/Asynchronous Prerequisite: (3 credits) CourseProfile (ATLAS), EECS 589. Students submit and present a thesis to be evaluated by the sponsoring faculty member and second reader. Eligibility is limited to students who have a concentration GPA of 3.5 or better. This course covers the fundamentals of patents for engineers. Instruction Mode: Hybrid – Synchronous, Online – Synchronous Introduction to probability and random processes. Minimum grade of C required for enforced prerequisites. Principles of light-emitting diodes, including transient effects, spectral and spatial radiation fields. (to be arranged) (3 credits) The mathematical tools required to describe spatial motion of a rigid body will be presented in full. CourseProfile (ATLAS), EECS 684. Data Science Seminar Case studies taken from current microprocessors. Analysis of circuit delay, power, and noise margins. Instruction Mode: Online – Synchronous 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. You should understand basic discrete mathematics including recursion relations, big-Oh Design of algorithms for nonnumeric problems involving sorting, searching, scheduling, graph theory and geometry. Advised Prerequisite: (MATH 115 or 116 or 119 or 120 or 121 or 156 or 175 or 176 or 185 or 186 or 214 or 215 or 216 or 217 or 255 or 256 or 285 or 286 or 295 or 296 or 417 or 419). (4 credits). (2 credits) Course goals include learning about important computational models of specific cognitive domains and evaluating the appropriateness and utility of different computational approaches to substantive problems in cognition. (3 credits) A substantial course project allows in-depth exploration of topics of interest. (3 credits) (3 credits) Enforced Prerequisite: EECS 370 and EECS 270 or graduate standing. Design rule checking, logic and circuit simulation. CourseProfile (ATLAS), EECS 180. CourseProfile (ATLAS), EECS 560 (AEROSP 550) (CEE 571) (MECHENG 564). Case studies. This course has no Matlab. Prerequisite: quantum mechanics, electrodynamics, atomic physics. College of Engineering - Recruitment and Admissions 153 Chrysler Center 2121 Bonisteel Boulevard Ann Arbor, MI 48109-2092 (734) 647-7101 email@example.com (3 credits) Each student must take (simultaneously) Tech Comm 496 (2 cr.) CourseProfile (ATLAS), EECS 381. Fundamental concepts in programming languages. Instruction Mode: Hybrid – Synchronous, Online – Synchronous Minimum grade of “C” required for enforced prerequisite. Advised prerequisite: permission of instructor. D-Algorithm and PODEM. Special Topics. CourseProfile (ATLAS), EECS 755. Basic concepts such as speedup, load balancing, latency, system taxonomies. (4 credits) Design of algorithms for idealized models. Sensor and actuator analysis and design through CAD. Readings from recent research papers. Instruction Mode: Online – Synchronous Polynomial time computability and paradigms of algorithm design. (3 credits) Minimum grade of “C” required for enforced prerequisites. Advanced very large scale integrated (VLSI) circuit design. Instruction Mode: Online – Synchronous Minimum grade of “C” required for enforced prerequisites. EECS Course Descriptions. CourseProfile (ATLAS), EECS 537 (APPPHYS 537). Instruction Mode: Online – Asynchronous The course presents both the theoretical and practical design, analysis, construction, and measurement of circuits and components in different types of power converters. CourseProfile (ATLAS), EECS 532 (CLIMATE 587). Special topics: nonlinear optics in fibers, including solitons and self-phase modulation. To be elected by EE and EES students pursuing the master’s thesis option. Topics include customer discovery, contextual inquiry, prototyping, process models, creative problem solving, inclusive thinking, team dynamics, social concerns, and testing strategies. Microstrip antennas. CourseProfile (ATLAS), EECS 285. Embedded Control Systems Techniques for routing and clock tree design. Prerequisite: Graduate standing and (EECS 402) and (EECS 203 or Math 465 or Math 565. (3 credits) (2-4 credits) CourseProfile (ATLAS), EECS 534. Good program design, structure and style are emphasized. Layout Synthesis and Optimization Design for testability. Grid Computing. Instruction Mode: Hybrid – Synchronous, Online – Synchronous Sensitivity, robustness, and design tradeoffs. Minimum grade of C for enforced prerequisites. Prerequisite: EECS 537 or EECS 538 or EECS 530. CourseProfile (ATLAS), EECS 522. (4 credits) Propagation, optical amplification and nonlinearities in fibers are discussed, and examples include transmission systems and lasers. Fading channels. (4 credits) Continuation of nonrelativistic quantum mechanics. EE students may select only EEC S301 to fulfill this requirement. Prerequisite: EECS 216 or graduate standing. Introduces social computing research, and relevant web-based tools for creating systems that allow multiple users to interact. Machine Learning Monolithic Amplifier Circuits AC machines, surface mount permanent magnet machines, induction machines. Prerequisite: permission of instructor. Prerequisite: EECS 330 or Physics 438. CourseProfile (ATLAS), EECS 547 (SI 652). Instruction Mode: Online – Synchronous Prerequisite: EECS 501, EECS 554. Prerequisite: ((Phys 240 or 260) and EECS 215 and EECS 216) or graduate standing. Prerequisite: EECS 501 and MATH 419. Propagation of ultrashort optical pulses in linear and nonlinear media, and through dispersive optical elements. Integration of electrical engineering foundational concepts to address system-level objectives. (4 credits) CourseProfile (ATLAS), EECS 568 (NAVARCH 568). See EECS course schedules, exam schedules, and book lists by semester. Production Systems Engineering Prerequisite: EECS 281 and (MATH 214 or 217 or 296 or 417 or 419) and (EECS 367 or EECS 373). The first part of the course focuses on the rules and codes that govern patent prosecution, and the second part focuses on claim drafting and amendment writing. Plasma Generation and Diagnostics Laboratory Students design and model complete converters. Analysis of Societal Networks Advanced micro electro mechanical systems (MEMS) devices and technologies. Image-based rendering. Instruction Mode: Online – Synchronous Theory of image formation and Fourier transformation by lenses. Prerequisites: EECS 592 or EECS 492. Oral presentation and/or written report due at end of term. Minimum grade of “C” required for enforced prerequisites. Elem Prog Concepts. Group projects. Digital Integrated Circuits Principles of Optics (4 credits) Discrete Event Systems Equalization. Wide-issue processors, in-order vs. out-of-order execution, instruction retirement. Plasmonics Using single and multiple inheritance and polymorphism for code reuse and extensibility; basic design idioms, patterns, and notation. Instruction Mode: Online – Synchronous Programming techniques in Standard C++ for large-scale, complex, or high-performance software. Instruction Mode: Online – Synchronous Integrated circuit fabrication overview, relationships between processing choices and device performance characteristics. May be taken more than once up to a total of 6 credit hours. Prerequisite: EECS 301 or graduate standing. CourseProfile (ATLAS), EECS 584. Acceleration algorithms: culling and level-of-detail. Stability considerations, pole-zero cancellation, root locus techniques in feedback amplifiers. (4 credits) Wire antennas: dipoles, loops and traveling-wave antennas. Topics include: Java syntax and semantics, object-oriented design, exception handling, graphical user interfaces, mobile-application development, asynchronous programming, and unit testing. CourseProfile (ATLAS), EECS 499. Electromagnetic Scattering Prerequisite: enrollment in the Masters of Engineering program in EECS. (3 credits) Complex hardware/software system design and implementation. CourseProfile (ATLAS), EECS 452. Instruction Mode: Online – Synchronous Operating system design and implementation: multi-tasking; concurrency and synchronization; inter-process communication; deadlock; scheduling; resource allocation; memory and storage management; input-output; file systems; protection and security. Introduction to Distributed Systems Advised prerequisite: Graduate standing. 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. Topics include cryptanalysis of classical cryptosystems; theoretical analysis of one-way functions; DES and differential cryptanalysis; the RSA cryptosystem; ElGamal, elliptic, hyperelliptic and hidden mononomial cryptosystems; attacks on signature schemes, identification schemes and authentication codes; secret sharing; and zero knowledge. Prerequisite: EECS 414. CourseProfile (ATLAS), EECS 576. Principles of engineering design for electrical engineering systems. Instruction Mode: Online – Synchronous 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. Highlights AES, RSA, Discrete Log, Elliptic Curves. VLSI Design II Ultrafast Optics Seminar in Solid-State Electronics Introduction; Course overview; (3 credits) CourseProfile (ATLAS), EECS 512. CourseProfile (ATLAS), EECS 586. (3 credits) Incentives and Strategic Behavior in Computational Systems CourseProfile (ATLAS), EECS 494. Detailed study of static current-voltage characteristics and models for small and large signal behavior. With a team of extremely dedicated and quality lecturers, eecs courses umich will not only be a place to share knowledge but also to help students get inspired to explore and discover many creative ideas from themselves. Hardware security assurance. Solid State Physics Analog Integrated Circuits Pulse width modulation. CourseProfile (ATLAS), EECS 525. Foundations of Computer Science Theory of digital modulation and coding. Laboratory involves CAD-based design implemented on an FPGA including elementary interfacing. Geometry, kinematics, differential kinematics, dynamics, and control of robot manipulators. Parallel Computing CourseProfile (ATLAS), EECS 535. Introduction to Digital Communication and Coding Theory: entropy for lossless coding; high-resolution theory for lossy coding. Models of computation: finite state machines, Turing machines. (1-6 credits) Topics of current interest selected by the faculty. Geometric and algebraic approaches to the analysis and design of nonlinear control systems. Functions and characteristics of the leading database management systems. CourseProfile (ATLAS), EECS 441. Geometrical and physical theories of diffraction. Current Topics in Databases Research issues in database systems chosen for in-depth study. Theoretical topics include subspaces, eigenvalue and singular value decomposition, projection theorem, constrained, regularized and unconstrained least squares techniques and iterative algorithms. Students develop and carry out a research plan in collaboration with a sponsoring faculty member. CourseProfile (ATLAS), EECS 430 (SPACE 431)(CLIMATE 431). Prerequisite: election of an EECS master’s thesis option. Required text: None. Course covers different programming languages including functional, imperative, object-oriented, and logic programming languages; different programming language features for naming, control flow, memory management, concurrency, and modularity; as well as methodologies, techniques and tools for writing correct and maintainable programs. Emphasizes construction of systems using graphics application programming interfaces (APIs) and analysis tools. Mask making, pattern transfer, oxidation, ion implantation and metallization. Sampling, filtering, 2D Fourier transforms, interpolation, edge detection, enhancement, denoising, restoration, segmentation, random field models of images, Bayesian methods, wavelets and sparsity models. (3 credits) This course covers the fundamentals of electric power distribution systems and electric loads, including distribution grid components, topologies, and operational strategies; three-phase unbalanced power flow; electric load modeling, analysis, and control; and emerging topics such as photovoltaic and electric vehicle interconnection, distribution automation, and advanced metering infrastructure. CourseProfile (ATLAS), EECS 502. Mediate, facilitate, or permission of instructor. ) the sponsoring faculty member and the chief advisor... To read and understand two 30-page research papers in artificial intelligence systems each Prerequisite! Limited to attempting each of the three 200-level courses ( EECS 270 or graduate standing (... Micromachined capacitive, piezoresistive and thermal limits in collaboration with a sponsoring faculty member second. Small eecs courses umich neural models and Psychological processes Prerequisite: ( EECS 421 permission... 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