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Author: Ruslan L. Stratonovich
Publisher: Springer Nature
ISBN: 3030228339
Category : Mathematics
Languages : en
Pages : 432
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Book Description
This English version of Ruslan L. Stratonovich’s Theory of Information (1975) builds on theory and provides methods, techniques, and concepts toward utilizing critical applications. Unifying theories of information, optimization, and statistical physics, the value of information theory has gained recognition in data science, machine learning, and artificial intelligence. With the emergence of a data-driven economy, progress in machine learning, artificial intelligence algorithms, and increased computational resources, the need for comprehending information is essential. This book is even more relevant today than when it was first published in 1975. It extends the classic work of R.L. Stratonovich, one of the original developers of the symmetrized version of stochastic calculus and filtering theory, to name just two topics. Each chapter begins with basic, fundamental ideas, supported by clear examples; the material then advances to great detail and depth. The reader is not required to be familiar with the more difficult and specific material. Rather, the treasure trove of examples of stochastic processes and problems makes this book accessible to a wide readership of researchers, postgraduates, and undergraduate students in mathematics, engineering, physics and computer science who are specializing in information theory, data analysis, or machine learning.
Author: Ruslan L. Stratonovich
Publisher: Springer Nature
ISBN: 3030228339
Category : Mathematics
Languages : en
Pages : 432
Get Book Here
Book Description
This English version of Ruslan L. Stratonovich’s Theory of Information (1975) builds on theory and provides methods, techniques, and concepts toward utilizing critical applications. Unifying theories of information, optimization, and statistical physics, the value of information theory has gained recognition in data science, machine learning, and artificial intelligence. With the emergence of a data-driven economy, progress in machine learning, artificial intelligence algorithms, and increased computational resources, the need for comprehending information is essential. This book is even more relevant today than when it was first published in 1975. It extends the classic work of R.L. Stratonovich, one of the original developers of the symmetrized version of stochastic calculus and filtering theory, to name just two topics. Each chapter begins with basic, fundamental ideas, supported by clear examples; the material then advances to great detail and depth. The reader is not required to be familiar with the more difficult and specific material. Rather, the treasure trove of examples of stochastic processes and problems makes this book accessible to a wide readership of researchers, postgraduates, and undergraduate students in mathematics, engineering, physics and computer science who are specializing in information theory, data analysis, or machine learning.
Author: George Gilder
Publisher: Regnery Publishing
ISBN: 1621570274
Category : Political Science
Languages : en
Pages : 370
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Book Description
Ronald Reagan’s most-quoted living author—George Gilder—is back with an all-new paradigm-shifting theory of capitalism that will upturn conventional wisdom, just when our economy desperately needs a new direction. America’s struggling economy needs a better philosophy than the college student's lament: "I can't be out of money, I still have checks in my checkbook!" We’ve tried a government spending spree, and we’ve learned it doesn’t work. Now is the time to rededicate our country to the pursuit of free market capitalism, before we’re buried under a mound of debt and unfunded entitlements. But how do we navigate between government spending that's too big to sustain and financial institutions that are "too big to fail?" In Knowledge and Power, George Gilder proposes a bold new theory on how capitalism produces wealth and how our economy can regain its vitality and its growth. Gilder breaks away from the supply-side model of economics to present a new economic paradigm: the epic conflict between the knowledge of entrepreneurs on one side, and the blunt power of government on the other. The knowledge of entrepreneurs, and their freedom to share and use that knowledge, are the sparks that light up the economy and set its gears in motion. The power of government to regulate, stifle, manipulate, subsidize or suppress knowledge and ideas is the inertia that slows those gears down, or keeps them from turning at all. One of the twentieth century’s defining economic minds has returned with a new philosophy to carry us into the twenty-first. Knowledge and Power is a must-read for fiscal conservatives, business owners, CEOs, investors, and anyone interested in propelling America’s economy to future success.
Author: Jeroen van den Hoven
Publisher: Cambridge University Press
ISBN: 9780521671613
Category : Philosophy
Languages : en
Pages : 428
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Book Description
This book gives an in-depth philosophical analysis of moral problems to which information technology gives rise, for example, problems related to privacy, intellectual property, responsibility, friendship, and trust, with contributions from many of the best-known philosophers writing in the area.
Author: Massimo Franceschetti
Publisher: Cambridge University Press
ISBN: 1107022312
Category : Computers
Languages : en
Pages : 477
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Book Description
An expert guide to the relationship between information theory and the physics of wave propagation, covering stochastic and deterministic approaches, engineering applications, and the universal physical limits of radiation. It is an ideal reference for researchers and graduate students in electrical engineering, physics, and applied mathematics.
Author: David Ellerman
Publisher: Springer Nature
ISBN: 3030865525
Category : Philosophy
Languages : en
Pages : 121
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Book Description
This monograph offers a new foundation for information theory that is based on the notion of information-as-distinctions, being directly measured by logical entropy, and on the re-quantification as Shannon entropy, which is the fundamental concept for the theory of coding and communications. Information is based on distinctions, differences, distinguishability, and diversity. Information sets are defined that express the distinctions made by a partition, e.g., the inverse-image of a random variable so they represent the pre-probability notion of information. Then logical entropy is a probability measure on the information sets, the probability that on two independent trials, a distinction or “dit” of the partition will be obtained. The formula for logical entropy is a new derivation of an old formula that goes back to the early twentieth century and has been re-derived many times in different contexts. As a probability measure, all the compound notions of joint, conditional, and mutual logical entropy are immediate. The Shannon entropy (which is not defined as a measure in the sense of measure theory) and its compound notions are then derived from a non-linear dit-to-bit transform that re-quantifies the distinctions of a random variable in terms of bits—so the Shannon entropy is the average number of binary distinctions or bits necessary to make all the distinctions of the random variable. And, using a linearization method, all the set concepts in this logical information theory naturally extend to vector spaces in general—and to Hilbert spaces in particular—for quantum logical information theory which provides the natural measure of the distinctions made in quantum measurement. Relatively short but dense in content, this work can be a reference to researchers and graduate students doing investigations in information theory, maximum entropy methods in physics, engineering, and statistics, and to all those with a special interest in a new approach to quantum information theory.
Author: JV Stone
Publisher: Sebtel Press
ISBN: 0956372856
Category : Business & Economics
Languages : en
Pages : 259
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Book Description
Originally developed by Claude Shannon in the 1940s, information theory laid the foundations for the digital revolution, and is now an essential tool in telecommunications, genetics, linguistics, brain sciences, and deep space communication. In this richly illustrated book, accessible examples are used to introduce information theory in terms of everyday games like ‘20 questions’ before more advanced topics are explored. Online MatLab and Python computer programs provide hands-on experience of information theory in action, and PowerPoint slides give support for teaching. Written in an informal style, with a comprehensive glossary and tutorial appendices, this text is an ideal primer for novices who wish to learn the essential principles and applications of information theory.
Author: Abbas El Gamal
Publisher: Cambridge University Press
ISBN: 1139503146
Category : Technology & Engineering
Languages : en
Pages : 666
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Book Description
This comprehensive treatment of network information theory and its applications provides the first unified coverage of both classical and recent results. With an approach that balances the introduction of new models and new coding techniques, readers are guided through Shannon's point-to-point information theory, single-hop networks, multihop networks, and extensions to distributed computing, secrecy, wireless communication, and networking. Elementary mathematical tools and techniques are used throughout, requiring only basic knowledge of probability, whilst unified proofs of coding theorems are based on a few simple lemmas, making the text accessible to newcomers. Key topics covered include successive cancellation and superposition coding, MIMO wireless communication, network coding, and cooperative relaying. Also covered are feedback and interactive communication, capacity approximations and scaling laws, and asynchronous and random access channels. This book is ideal for use in the classroom, for self-study, and as a reference for researchers and engineers in industry and academia.
Author: Thomas M. Cover
Publisher: John Wiley & Sons
ISBN: 1118585771
Category : Computers
Languages : en
Pages : 788
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Book Description
The latest edition of this classic is updated with new problem sets and material The Second Edition of this fundamental textbook maintains the book's tradition of clear, thought-provoking instruction. Readers are provided once again with an instructive mix of mathematics, physics, statistics, and information theory. All the essential topics in information theory are covered in detail, including entropy, data compression, channel capacity, rate distortion, network information theory, and hypothesis testing. The authors provide readers with a solid understanding of the underlying theory and applications. Problem sets and a telegraphic summary at the end of each chapter further assist readers. The historical notes that follow each chapter recap the main points. The Second Edition features: * Chapters reorganized to improve teaching * 200 new problems * New material on source coding, portfolio theory, and feedback capacity * Updated references Now current and enhanced, the Second Edition of Elements of Information Theory remains the ideal textbook for upper-level undergraduate and graduate courses in electrical engineering, statistics, and telecommunications.
Author: Robert M. Gray
Publisher: Springer Science & Business Media
ISBN: 1475739826
Category : Computers
Languages : en
Pages : 346
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Book Description
This book is devoted to the theory of probabilistic information measures and their application to coding theorems for information sources and noisy channels. The eventual goal is a general development of Shannon's mathematical theory of communication, but much of the space is devoted to the tools and methods required to prove the Shannon coding theorems. These tools form an area common to ergodic theory and information theory and comprise several quantitative notions of the information in random variables, random processes, and dynamical systems. Examples are entropy, mutual information, conditional entropy, conditional information, and discrimination or relative entropy, along with the limiting normalized versions of these quantities such as entropy rate and information rate. Much of the book is concerned with their properties, especially the long term asymptotic behavior of sample information and expected information. This is the only up-to-date treatment of traditional information theory emphasizing ergodic theory.
Author: Mark Burgin
Publisher: World Scientific
ISBN: 9812835482
Category : Computers
Languages : en
Pages : 689
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Book Description
Presents a fresh approach to scientific understanding of information phenomena. Based on an analysis of information processes in nature, technology, and society, as well as on the main directions in information theory, this book offers a theory that synthesizes various directions into a unified system.
