Discover new theoretical connections between stochastic phenomena and the structure of natural language with this powerful volume! Information Theory Meets Power Laws: Stochastic Processes and Language Models presents readers with a novel subtype of a probabilistic approach to language, which is based on statistical laws of texts and their analysis by means of information theory. The distinguished author insightfully and rigorously examines the linguistic and mathematical subject matter while eschewing needlessly abstract and superfluous constructions. The book begins with a less formal treatment of its subjects in the first chapter, introducing its concepts to readers without mathematical training and allowing those unfamiliar with linguistics to learn the book’s motivations. Despite its inherent complexity, Information Theory Meets Power Laws: Stochastic Processes and Language Models is a surprisingly approachable treatment of idealized mathematical models of human language. The author succeeds in developing some of the theory underlying fundamental stochastic and semantic phenomena, like strong nonergodicity, in a way that has not previously been seriously attempted. In doing so, he covers topics including: Zipf’s and Herdan’s laws for natural language Power laws for information, repetitions, and correlations Markov, finite-state,and Santa Fe processes Bayesian and frequentist interpretations of probability Ergodic decomposition, Kolmogorov complexity, and universal coding Theorems about facts and words Information measures for fields Rényi entropies, recurrence times, and subword complexity Asymptotically mean stationary processes Written primarily for mathematics graduate students and professionals interested in information theory or discrete stochastic processes, Information Theory Meets Power Laws: Stochastic Processes and Language Models also belongs on the bookshelves of doctoral students and researchers in artificial intelligence, computational and quantitative linguistics as well as physics of complex systems.

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.

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.

This book provides a comprehensive description of a new method of proving the central limit theorem, through the use of apparently unrelated results from information theory. It gives a basic introduction to the concepts of entropy and Fisher information, and collects together standard results concerning their behaviour. It brings together results from a number of research papers as well as unpublished material, showing how the techniques can give a unified view of limit theorems.

A very active field of research is emerging at the frontier of statistical physics, theoretical computer science/discrete mathematics, and coding/information theory. This book sets up a common language and pool of concepts, accessible to students and researchers from each of these fields.

This highly interdisciplinary book discusses the phenomenon of life, including its origin and evolution, against the background of thermodynamics, statistical mechanics, and information theory. Among the central themes is the seeming contradiction between the second law of thermodynamics and the high degree of order and complexity produced by living systems. As the author shows, this paradox has its resolution in the information content of the Gibbs free energy that enters the biosphere from outside sources. Another focus of the book is the role of information in human cultural evolution, which is also discussed with the origin of human linguistic abilities. One of the final chapters addresses the merging of information technology and biotechnology into a new discipline — bioinformation technology.This third edition has been updated to reflect the latest scientific and technological advances. Professor Avery makes use of the perspectives of famous scholars such as Professor Noam Chomsky and Nobel Laureates John O'Keefe, May-Britt Moser and Edward Moser to cast light on the evolution of human languages. The mechanism of cell differentiation, and the rapid acceleration of information technology in the 21st century are also discussed.With various research disciplines becoming increasingly interrelated today, Information Theory and Evolution provides nuance to the conversation between bioinformatics, information technology, and pertinent social-political issues. This book is a welcome voice in working on the future challenges that humanity will face as a result of scientific and technological progress.

A self-contained, graduate-level textbook that develops from scratch classical results as well as advances of the past decade.

Information Theory: Coding Theorems for Discrete Memoryless Systems presents mathematical models that involve independent random variables with finite range. This three-chapter text specifically describes the characteristic phenomena of information theory. Chapter 1 deals with information measures in simple coding problems, with emphasis on some formal properties of Shannon's information and the non-block source coding. Chapter 2 describes the properties and practical aspects of the two-terminal systems. This chapter also examines the noisy channel coding problem, the computation of channel capacity, and the arbitrarily varying channels. Chapter 3 looks into the theory and practicality of multi-terminal systems. This book is intended primarily for graduate students and research workers in mathematics, electrical engineering, and computer science.

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.