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Published by: Massachusetts Institute of Technology | Language: English
Published by: Massachusetts Institute of Technology | Language: English
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The major themes of this course are estimation and control of dynamic systems. Preliminary topics begin with reviews of probability and random variables. Next, classical and state-space descriptions of random processes and their propagation through linear systems are introduced, followed by frequency domain design of filters and compensator
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- aeronautics and astronautics
- probability
- stochastic estimation
- estimation
- random variables
- random processes
- state space
- wiener filter
- control system design
- kalman filter
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Published by: Massachusetts Institute of Technology | Language: English
Published by: Massachusetts Institute of Technology | Language: English
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This subject is a computer-oriented introduction to probability and data analysis. It is designed to give students the knowledge and practical experience they need to interpret lab and field data. Basic probability concepts are introduced at the outset because they provide a systematic way to describe uncertainty. They form the basis for th
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Tag(s):
- civil and environmental engineering
- probability
- statistics
- events
- random variables
- univariate distributions
- multivariate distributions
- uncertainty propagation
- bernoulli trials
- poisson processed
- conditional probability
- bayes rule
- random sampling
- point estimation
- interval estimation
- hypothesis testing
- analysis of variance
- linear regression
- computational analysi
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Published by: Massachusetts Institute of Technology | Language: English
Published by: Massachusetts Institute of Technology | Language: English
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Welcome to 6.041/6.431, a subject on the modeling and analysis of random phenomena and processes, including the basics of statistical inference. Nowadays, there is broad consensus that the ability to think probabilistically is a fundamental component of scientific literacy. For example: The concept of statistical significance (to be to
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Tag(s):
- electrical engineering and computer science
- probability
- probability models
- bayes rule
- discrete random variables
- continuous random variables
- bernoulli process
- poisson process
- markov chains
- central limit theorem
- statistical inference
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Published by: Massachusetts Institute of Technology | Language: English
Published by: Massachusetts Institute of Technology | Language: English
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Discrete stochastic processes are essentially probabilistic systems that evolve in time via random changes occurring at discrete fixed or random intervals. This course aims to help students acquire both the mathematical principles and the intuition necessary to create, analyze, and understand insightful models for a broad range of these pro
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Tag(s):
- electrical engineering and computer science
- probability
- poisson processes
- finite-state markov chains
- renewal processes
- countable-state markov chains
- markov processes
- countable state spaces
- random walks
- large deviations
- martingales
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Published by: Massachusetts Institute of Technology | Language: English
Published by: Massachusetts Institute of Technology | Language: English
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This course offers an introduction to probability, statistical mechanics, and thermodynamics. Numerous examples are used to illustrate a wide variety of physical phenomena such as magnetism, polyatomic gases, thermal radiation, electrons in solids, and noise in electronic devices.
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Tag(s):
- physics
- probability
- statistical mechanics
- thermodynamics
- random variables
- joint and conditional probability densities
- functions of a random variable
- macroscopic variables
- thermodynamic equilibrium
- fundamental assumption of statistical mechanics
- microcanonical and canonical ensembles
- first
- second
- and third laws of thermodynamics
- magneti
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