Probability in Electrical Engineering and Computer Science

This revised textbook motivates and illustrates the techniques of applied probability by applications in electrical engineering and computer science (EECS). The author presents information processing and communication systems that use algorithms based on probabilistic models and techniques, includin...

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Auteur principal: Walrand, Jean
Format: Online
Langue:anglais
Publié: Springer Nature 2021
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Accès en ligne:ONIX_20210714_9783030499952_7
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author Walrand, Jean
author_browse Walrand, Jean
author_facet Walrand, Jean
author_sort Walrand, Jean
collection Directory of Open Access Books
description This revised textbook motivates and illustrates the techniques of applied probability by applications in electrical engineering and computer science (EECS). The author presents information processing and communication systems that use algorithms based on probabilistic models and techniques, including web searches, digital links, speech recognition, GPS, route planning, recommendation systems, classification, and estimation. He then explains how these applications work and, along the way, provides the readers with the understanding of the key concepts and methods of applied probability. Python labs enable the readers to experiment and consolidate their understanding. The book includes homework, solutions, and Jupyter notebooks. This edition includes new topics such as Boosting, Multi-armed bandits, statistical tests, social networks, queuing networks, and neural networks. For ancillaries related to this book, including examples of Python demos and also Python labs used in Berkeley, please email Mary James at [email protected]. This is an open access book.
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spelling doab-20.500.12854ir-712972025-08-13T14:12:29Z Probability in Electrical Engineering and Computer Science Walrand, Jean Probability and Statistics in Computer Science Communications Engineering, Networks Mathematical and Computational Engineering Probability Theory and Stochastic Processes Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences Mathematical and Computational Engineering Applications Probability Theory Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences Applied probability Hypothesis testing Detection theory Expectation maximization Stochastic dynamic programming Machine learning Stochastic gradient descent Deep neural networks Matrix completion Linear and polynomial regression Open Access Maths for computer scientists Mathematical & statistical software Communications engineering / telecommunications Maths for engineers Probability & statistics Stochastics Textbook thema EDItEUR::U Computing and Information Technology::UY Computer science::UYA Mathematical theory of computation::UYAM Maths for computer scientists thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJK Communications engineering / telecommunications thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBJ Maths for engineers thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics thema EDItEUR::U Computing and Information Technology::UY Computer science::UYA Mathematical theory of computation::UYAM Maths for computer scientists thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJK Communications engineering / telecommunications thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBJ Maths for engineers thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics This revised textbook motivates and illustrates the techniques of applied probability by applications in electrical engineering and computer science (EECS). The author presents information processing and communication systems that use algorithms based on probabilistic models and techniques, including web searches, digital links, speech recognition, GPS, route planning, recommendation systems, classification, and estimation. He then explains how these applications work and, along the way, provides the readers with the understanding of the key concepts and methods of applied probability. Python labs enable the readers to experiment and consolidate their understanding. The book includes homework, solutions, and Jupyter notebooks. This edition includes new topics such as Boosting, Multi-armed bandits, statistical tests, social networks, queuing networks, and neural networks. For ancillaries related to this book, including examples of Python demos and also Python labs used in Berkeley, please email Mary James at [email protected]. This is an open access book. 2021-07-15T02:01:05Z 2021-07-15T02:01:05Z 2021-07-14T09:58:07Z 2021 book ONIX_20210714_9783030499952_7 OCN: 1258658362 https://library.oapen.org/handle/20.500.12657/50016 9783030499952 https://directory.doabooks.org/handle/20.500.12854/71297 eng open access image/jpeg image/jpeg image/jpeg n/a n/a n/a https://library.oapen.org/bitstream/20.500.12657/50016/1/978-3-030-49995-2.pdf https://library.oapen.org/bitstream/20.500.12657/50016/1/978-3-030-49995-2.pdf https://library.oapen.org/bitstream/20.500.12657/50016/1/978-3-030-49995-2.pdf Springer Nature Springer International Publishing 10.1007/978-3-030-49995-2 10.1007/978-3-030-49995-2 9fa3421d-f917-4153-b9ab-fc337c396b5a University of California, Berkeley Foundation 1edf7275-d11e-45ad-a038-9270d4ffa2e0 9783030499952 Springer International Publishing 380 [grantnumber unknown] open access
spellingShingle Probability and Statistics in Computer Science
Communications Engineering, Networks
Mathematical and Computational Engineering
Probability Theory and Stochastic Processes
Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
Mathematical and Computational Engineering Applications
Probability Theory
Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences
Applied probability
Hypothesis testing
Detection theory
Expectation maximization
Stochastic dynamic programming
Machine learning
Stochastic gradient descent
Deep neural networks
Matrix completion
Linear and polynomial regression
Open Access
Maths for computer scientists
Mathematical & statistical software
Communications engineering / telecommunications
Maths for engineers
Probability & statistics
Stochastics
Textbook
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYA Mathematical theory of computation::UYAM Maths for computer scientists
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJK Communications engineering / telecommunications
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBJ Maths for engineers
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYA Mathematical theory of computation::UYAM Maths for computer scientists
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJK Communications engineering / telecommunications
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBJ Maths for engineers
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics
Walrand, Jean
Probability in Electrical Engineering and Computer Science
title Probability in Electrical Engineering and Computer Science
title_full Probability in Electrical Engineering and Computer Science
title_fullStr Probability in Electrical Engineering and Computer Science
title_full_unstemmed Probability in Electrical Engineering and Computer Science
title_short Probability in Electrical Engineering and Computer Science
title_sort probability in electrical engineering and computer science
topic Probability and Statistics in Computer Science
Communications Engineering, Networks
Mathematical and Computational Engineering
Probability Theory and Stochastic Processes
Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
Mathematical and Computational Engineering Applications
Probability Theory
Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences
Applied probability
Hypothesis testing
Detection theory
Expectation maximization
Stochastic dynamic programming
Machine learning
Stochastic gradient descent
Deep neural networks
Matrix completion
Linear and polynomial regression
Open Access
Maths for computer scientists
Mathematical & statistical software
Communications engineering / telecommunications
Maths for engineers
Probability & statistics
Stochastics
Textbook
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYA Mathematical theory of computation::UYAM Maths for computer scientists
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJK Communications engineering / telecommunications
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBJ Maths for engineers
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYA Mathematical theory of computation::UYAM Maths for computer scientists
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJK Communications engineering / telecommunications
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBJ Maths for engineers
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics
topic_facet Probability and Statistics in Computer Science
Communications Engineering, Networks
Mathematical and Computational Engineering
Probability Theory and Stochastic Processes
Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
Mathematical and Computational Engineering Applications
Probability Theory
Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences
Applied probability
Hypothesis testing
Detection theory
Expectation maximization
Stochastic dynamic programming
Machine learning
Stochastic gradient descent
Deep neural networks
Matrix completion
Linear and polynomial regression
Open Access
Maths for computer scientists
Mathematical & statistical software
Communications engineering / telecommunications
Maths for engineers
Probability & statistics
Stochastics
Textbook
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYA Mathematical theory of computation::UYAM Maths for computer scientists
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJK Communications engineering / telecommunications
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBJ Maths for engineers
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYA Mathematical theory of computation::UYAM Maths for computer scientists
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJK Communications engineering / telecommunications
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBJ Maths for engineers
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics
url ONIX_20210714_9783030499952_7
work_keys_str_mv AT walrandjean probabilityinelectricalengineeringandcomputerscience