Courses tagged with "Information environments" (1105)

This course is devoted to the theory of Lie Groups with emphasis on its connections with Differential Geometry. The text for this class is Differential Geometry, Lie Groups and Symmetric Spaces by Sigurdur Helgason (American Mathematical Society, 2001).

Much of the course material is based on Chapter I (first half) and Chapter II of the text. The text however develops basic Riemannian Geometry, Complex Manifolds, as well as a detailed theory of Semisimple Lie Groups and Symmetric Spaces.

This course provides ways to analyze manufacturing systems in terms of material flow and storage, information flow, capacities, and times and durations of events. Fundamental topics include probability, inventory and queuing models, optimization, and linear and dynamic systems. Factory planning and scheduling topics include flow planning, bottleneck characterization, buffer and batch-size analysis, and dynamic behavior of production systems.

This course is an introduction to linear optimization and its extensions emphasizing the underlying mathematical structures, geometrical ideas, algorithms and solutions of practical problems. The topics covered include: formulations, the geometry of linear optimization, duality theory, the simplex method, sensitivity analysis, robust optimization, large scale optimization network flows, solving problems with an exponential number of constraints and the ellipsoid method, interior point methods, semidefinite optimization, solving real world problems problems with computer software, discrete optimization formulations and algorithms.

Traditionally, progress in electronics has been driven by miniaturization. But as electronic devices approach the molecular scale, classical models for device behavior must be abandoned. To prepare for the next generation of electronic devices, this class teaches the theory of current, voltage and resistance from atoms up. To describe electrons at the nanoscale, we will begin with an introduction to the principles of quantum mechanics, including quantization, the wave-particle duality, wavefunctions and Schrödinger's equation. Then we will consider the electronic properties of molecules, carbon nanotubes and crystals, including energy band formation and the origin of metals, insulators and semiconductors. Electron conduction will be taught beginning with ballistic transport and concluding with a derivation of Ohm's law. We will then compare ballistic to bulk MOSFETs. The class will conclude with a discussion of possible fundamental limits to computation.

This course explores the organization of synaptic connectivity as the basis of neural computation and learning. Perceptrons and dynamical theories of recurrent networks including amplifiers, attractors, and hybrid computation are covered. Additional topics include backpropagation and Hebbian learning, as well as models of perception, motor control, memory, and neural development.

The course will span modern neuroscience from molecular neurobiology to perception and cognition, including the following major topics: anatomy and development of the brain; cell biology of neurons and glia; ion channels and electrical signaling; synaptic transmission, integration, and chemical systems of the brain; sensory systems, from transduction to perception; motor systems; and higher brain functions dealing with memory, language, and affective disorders.

The phenomenology and experimental foundations of particle and nuclear physics are explored in this course. Emphasis is on the fundamental forces and particles, as well as composites.

This course offers an advanced introduction to numerical linear algebra. Topics include direct and iterative methods for linear systems, eigenvalue decompositions and QR/SVD factorizations, stability and accuracy of numerical algorithms, the IEEE floating point standard, sparse and structured matrices, preconditioning, linear algebra software. Problem sets require some knowledge of MATLAB®.

This course offers an advanced introduction to numerical linear algebra. Topics include direct and iterative methods for linear systems, eigenvalue decompositions and QR/SVD factorizations, stability and accuracy of numerical algorithms, the IEEE floating point standard, sparse and structured matrices, preconditioning, linear algebra software. Problem sets require some knowledge of MATLAB®.

6.336J is an introduction to computational techniques for the simulation of a large variety of engineering and physical systems. Applications are drawn from aerospace, mechanical, electrical, chemical and biological engineering, and materials science. Topics include: mathematical formulations; network problems; sparse direct and iterative matrix solution techniques; Newton methods for nonlinear problems; discretization methods for ordinary, time-periodic and partial differential equations, fast methods for partial differential and integral equations, techniques for dynamical system model reduction and approaches for molecular dynamics.

This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5211 (Introduction to Numerical Simulation).

Observational physical oceanography includes topics such as the  physical description of the sea, the physical properties of seawater, methods and measurements, wind-driven ocean circulation, abyssal ocean circulation, boundary processes, and wave motions.

This half-term course introduces students to problems and analysis related to the design, planning, control, and improvement of manufacturing and service operations. Class sessions involve explaining concepts, working examples, and discussing cases. A wide range of topics are covered, including: process analysis, quality management, supply chain design, procurement, and product development. Toward the end of the course, students work in teams to manage a virtual factory in a web-based simulation exercise.

This course provides students with concepts, techniques and tools to design, analyze, and improve core operational capabilities, and apply them to a broad range of application domains and industries. It emphasizes the effect of uncertainty in decision-making, as well as the interplay between high-level financial objectives and operational capabilities. Topics covered include production control, risk pooling, quality management, process design, and revenue management. Also included are case studies, guest lectures, and simulation games which demonstrate central concepts.

This course serves as an introduction to the current research questions in phonological theory. Topics include metrical and prosodic structure, features and their phonetic basis in speech, acquisition and parsing, phonological domains, morphology, and language change and reconstruction. Activities include problem solving, squibs, and data collection.

The plasma state dominates the visible universe, and is important in fields as diverse as Astrophysics and Controlled Fusion. Plasma is often referred to as "the fourth state of matter." This course introduces the study of the nature and behavior of plasma. A variety of models to describe plasma behavior are presented.

The plasma state dominates the visible universe, and is important in fields as diverse as Astrophysics and Controlled Fusion. Plasma is often referred to as "the fourth state of matter." This course introduces the study of the nature and behavior of plasma. A variety of models to describe plasma behavior are presented.

This graduate level course presents a basic study in seismology and the utilization of seismic waves for the study of Earth's interior. It introduces techniques necessary for understanding of elastic wave propagation in layered media.

This course is an introduction to Markov chains, random walks, martingales, and Galton-Watsom tree. The course requires basic knowledge in probability theory and linear algebra including conditional expectation and matrix.

This class assesses current and potential future energy systems, covering resources, extraction, conversion, and end-use technologies, with emphasis on meeting regional and global energy needs in the 21st century in a sustainable manner. Instructors and guest lecturers will examine various renewable and conventional energy production technologies, energy end-use practices and alternatives, and consumption practices in different countries. Students will learn a quantitative framework to aid in evaluation and analysis of energy technology system proposals in the context of engineering, political, social, economic, and environmental goals. Students taking the graduate version, Sustainable Energy, complete additional assignments.

This course is concerned with the concepts and principles which have been of central significance in the recent development of syntactic theory, with special focus on the "Government and Binding" (GB) / "Principles and Parameters" (P&P) / "Minimalist Program" (MP) approach.

It is the first of a series of two courses (24.951 is taught during the Fall and 24.952 is taught in the Spring). This course deals mostly with phrase structure, argument structure and its syntactic expression, including "A-movement". Though other issues (e.g. wh-movement, antecedent-contained deletion, extraposition) may be mentioned during the semester, the course will not systematically investigate these topics in class until 24.952.

The goal of the course is to understand why certain problems have been treated in certain ways. Thus, on many occasions a variety of approaches will be discussed, and the (recent) historical development of these approaches are emphasized.