Courses tagged with "Before 1300: Ancient and Medieval History" (148)

This course provides an introduction to the design of feedback systems. Topics covered include: properties and advantages of feedback systems, time-domain and frequency-domain performance measures, stability and degree of stability, root locus method, Nyquist criterion, frequency-domain design, compensation techniques, application to a wide variety of physical systems, internal and external compensation of operational amplifiers, modeling and compensation of power converter systems, and phase lock loops.

This course explores the fundamentals of optical and optoelectronic phenomena and devices based on classical and quantum properties of radiation and matter culminating in lasers and applications. Fundamentals include: Maxwell's electromagnetic waves, resonators and beams, classical ray optics and optical systems, quantum theory of light, matter and its interaction, classical and quantum noise, lasers and laser dynamics, continuous wave and short pulse generation, light modulation; examples from integrated optics and semiconductor optoelectronics and nonlinear optics.

This is a course on the fundamentals of probability geared towards first- or second-year graduate students who are interested in a rigorous development of the subject. The course covers most of the topics in 6.431 (sample space, random variables, expectations, transforms, Bernoulli and Poisson processes, finite Markov chains, limit theorems) but at a faster pace and in more depth. There are also a number of additional topics, such as language, terminology, and key results from measure theory; interchange of limits and expectations; multivariate Gaussian distributions; deeper understanding of conditional distributions and expectations.

This course is an introduction to the fundamentals of game theory and mechanism design. Motivations are drawn from engineered/networked systems (including distributed control of wireline and wireless communication networks, incentive-compatible/dynamic resource allocation, multi-agent systems, pricing and investment decisions in the Internet), and social models (including social and economic networks). The course emphasizes theoretical foundations, mathematical tools, modeling, and equilibrium notions in different environments.

This course provides a challenging introduction to some of the central ideas of theoretical computer science. It attempts to present a vision of "computer science beyond computers": that is, CS as a set of mathematical tools for understanding complex systems such as universes and minds. Beginning in antiquity—with Euclid's algorithm and other ancient examples of computational thinking—the course will progress rapidly through propositional logic, Turing machines and computability, finite automata, Gödel's theorems, efficient algorithms and reducibility, NP-completeness, the P versus NP problem, decision trees and other concrete computational models, the power of randomness, cryptography and one-way functions, computational theories of learning, interactive proofs, and quantum computing and the physical limits of computation. Class participation is essential, as the class will include discussion and debate about the implications of many of these ideas.

This course introduces students to both passive and active electronic components (op-amps, 555 timers, TTL digital circuits). Basic analog and digital circuits and theory of operation are covered. The labs allow the students to master the use of electronic instruments and construct and/or solder several circuits. The labs also reinforce the concepts discussed in class with a hands-on approach and allow the students to gain significant experience with electrical instruments such as function generators, digital multimeters, oscilloscopes, logic analyzers and power supplies. In the last lab, the students build an electronic circuit that they can keep. The course is geared to freshmen and others who want an introduction to electronics circuits.

This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month.

6.776 covers circuit level design issues of high speed communication systems, with primary focus being placed on wireless and broadband data link applications. Specific circuit topics include transmission lines, high speed and low noise amplifiers, VCO's, mixers, power amps, high speed digital circuits, and frequency synthesizers. In addition to learning analysis skills for the above items, students will gain a significant amount of experience in simulating RF circuits in SPICE and also building RF circuits within a lab project.

This course explores the ultimate limits to communication and computation, with an emphasis on the physical nature of information and information processing. Topics include: information and computation, digital signals, codes and compression, applications such as biological representations of information, logic circuits, computer architectures, and algorithmic information, noise, probability, error correction, reversible and irreversible operations, physics of computation, and quantum computation. The concept of entropy applied to channel capacity and to the second law of thermodynamics.

This is a graduate-level introduction to mathematics of information theory. We will cover both classical and modern topics, including information entropy, lossless data compression, binary hypothesis testing, channel coding, and lossy data compression.

6.720 examines the physics of microelectronic semiconductor devices for silicon integrated circuit applications. Topics covered include: semiconductor fundamentals, p-n junction, metal-oxide semiconductor structure, metal-semiconductor junction, MOS field-effect transistor, and bipolar junction transistor. The course emphasizes physical understanding of device operation through energy band diagrams and short-channel MOSFET device design. Issues in modern device scaling are also outlined. The course is worth 2 Engineering Design Points.

Acknowledgments

Prof. Jesús del Alamo would like to thank Prof. Harry Tuller for his support of and help in teaching the course.

This course provides an introduction to mathematical modeling of computational problems. It covers the common algorithms, algorithmic paradigms, and data structures used to solve these problems. The course emphasizes the relationship between algorithms and programming, and introduces basic performance measures and analysis techniques for these problems.

Ever hang your head in shame after your Python program wasn't as fast as your friend's C program? Ever wish you could use objects without having to use Java? Join us for this fun introduction to C and C++! We will take you through a tour that will start with writing simple C programs, go deep into the caves of C memory manipulation, resurface with an introduction to using C++ classes, dive deeper into advanced C++ class use and the C++ Standard Template Libraries. We'll wrap up by teaching you some tricks of the trade that you may need for tech interviews.

We see this as a "C/C++ empowerment" course: we want you to come away understanding

1. why you would want to use C over another language (control over memory, probably for performance reasons),
2. why you would want to use C++ rather than C (objects), and
3. how to be useful in C and C++.

This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month.

This is a fast-paced introductory course to the C++ programming language. It is intended for those with little programming background, though prior programming experience will make it easier, and those with previous experience will still learn C++-specific constructs and concepts.

This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month.

This course examines signals, systems and inference as unifying themes in communication, control and signal processing. Topics include input-output and state-space models of linear systems driven by deterministic and random signals; time- and transform-domain representations in discrete and continuous time; group delay; state feedback and observers; probabilistic models; stochastic processes, correlation functions, power spectra, spectral factorization; least-mean square error estimation; Wiener filtering; hypothesis testing; detection; matched filters.

This subject is aimed at students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems. It also aims to help students, regardless of their major, to feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class will use the Python™ programming language.

This subject is aimed at students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems. It also aims to help students, regardless of their major, to feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class will use the Python programming language.

Course Format

This course has been designed for independent study. It provides everything you will need to understand the concepts covered in the course. The materials include:

• A complete set of Lecture Videos by Prof. Guttag.
• Resources for each lecture video, such as Handouts, Slides, and Code Files.
• Recitation Videos by course TA's to review content and problem solving techniques.
• Homework problems with sample student solutions.
• Further Study collections of links to supplemental online content.
• Self-Assessment tools, including lecture questions with answers and unit quizzes with solutions, to assess your subject mastery.