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Author: Kofi Kissi Dompere Publisher: Springer ISBN: 3030181596 Category : Technology & Engineering Languages : en Pages : 286
Book Description
This book presents an epistemic framework for dealing with information-knowledge and certainty-uncertainty problems within the space of quality-quantity dualities. It bridges between theoretical concepts of entropy and entropy measurements, proposing the concept and measurement of fuzzy-stochastic entropy that is applicable to all areas of knowing under human cognitive limitations over the epistemological space. The book builds on two previous monographs by the same author concerning theories of info-statics and info-dynamics, to deal with identification and transformation problems respectively. The theoretical framework is developed by using the toolboxes such as those of the principle of opposites, systems of actual-potential polarities and negative-positive dualities, under different cost-benefit time-structures. The category theory and the fuzzy paradigm of thought, under methodological constructionism-reductionism duality, are used in the fuzzy-stochastic and cost-benefit spaces to point to directions of global application in knowing, knowledge and decision-choice actions. Thus, the book is concerned with a general theory of entropy, showing how the fuzzy paradigm of thought is developed to deal with the problems of qualitative-quantitative uncertainties over the fuzzy-stochastic space, which will be applicable to conditions of soft-hard data, fact, evidence and knowledge over the spaces of problem-solution dualities, decision-choice actions in sciences, non-sciences, engineering and planning sciences to abstract acceptable information-knowledge elements.
Author: Kofi Kissi Dompere Publisher: Springer ISBN: 3030181596 Category : Technology & Engineering Languages : en Pages : 286
Book Description
This book presents an epistemic framework for dealing with information-knowledge and certainty-uncertainty problems within the space of quality-quantity dualities. It bridges between theoretical concepts of entropy and entropy measurements, proposing the concept and measurement of fuzzy-stochastic entropy that is applicable to all areas of knowing under human cognitive limitations over the epistemological space. The book builds on two previous monographs by the same author concerning theories of info-statics and info-dynamics, to deal with identification and transformation problems respectively. The theoretical framework is developed by using the toolboxes such as those of the principle of opposites, systems of actual-potential polarities and negative-positive dualities, under different cost-benefit time-structures. The category theory and the fuzzy paradigm of thought, under methodological constructionism-reductionism duality, are used in the fuzzy-stochastic and cost-benefit spaces to point to directions of global application in knowing, knowledge and decision-choice actions. Thus, the book is concerned with a general theory of entropy, showing how the fuzzy paradigm of thought is developed to deal with the problems of qualitative-quantitative uncertainties over the fuzzy-stochastic space, which will be applicable to conditions of soft-hard data, fact, evidence and knowledge over the spaces of problem-solution dualities, decision-choice actions in sciences, non-sciences, engineering and planning sciences to abstract acceptable information-knowledge elements.
Author: Kenneth D. Bailey Publisher: SUNY Press ISBN: 9780791400562 Category : Social Science Languages : en Pages : 336
Book Description
Social Entropy Theory illuminates the fundamental problems of societal analysis with a nonequilibrium approach, a new frame of reference built upon contemporary macrological principles, including general systems theory and information theory. Social entropy theory, using Shannon's H and the entropy concept, avoids the common (and often artificial) separation of theory and method in sociology. The hallmark of the volume is integration, as seen in the author's interdisciplinary discussions of equilibrium, entropy, and homeostasis. Unique features of the book are the introduction of the three-level model of social measurement, the theory of allocation, the concepts of global-mutable-immutable, discussion of order and power, and a large set of testable hypotheses.
Author: Robert M. Gray Publisher: Springer Science & Business Media ISBN: 1475739826 Category : Computers Languages : en Pages : 346
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: Arieh Ben-naim Publisher: World Scientific ISBN: 9814465267 Category : Science Languages : en Pages : 287
Book Description
This is a sequel to the author's book entitled “Entropy Demystified” (Published by World Scientific, 2007). The aim is essentially the same as that of the previous book by the author: to present Entropy and the Second Law as simple, meaningful and comprehensible concepts. In addition, this book presents a series of “experiments” which are designed to help the reader discover entropy and the Second Law. While doing the experiments, the reader will encounter three most fundamental probability distributions featuring in Physics: the Uniform, the Boltzmann and the Maxwell-Boltzmann distributions. In addition, the concepts of entropy and the Second Law will emerge naturally from these experiments without a tinge of mystery. These concepts are explained with the help of a few familiar ideas of probability and information theory.The main “value” of the book is to introduce entropy and the Second Law in simple language which renders it accessible to any reader who can read and is curious about the basic laws of nature. The book is addressed to anyone interested in science and in understanding natural phenomenon. It will afford the reader the opportunity to discover one of the most fundamental laws of physics — a law that has resisted complete understanding for over a century. The book is also designed to be enjoyable.There is no other book of its kind (except “Entropy Demystified” by the same author) that offers the reader a unique opportunity to discover one of the most profound laws — sometimes viewed as a mysterious — while comfortably playing with familiar games. There are no pre-requisites expected from the readers; all that the reader is expected to do is to follow the experiments or imagine doing the experiments and reach the inevitable conclusions.
Author: Samuel M. Scheiner Publisher: University of Chicago Press ISBN: 0226736865 Category : Science Languages : en Pages : 416
Book Description
Despite claims to the contrary, the science of ecology has a long history of building theories. Many ecological theories are mathematical, computational, or statistical, though, and rarely have attempts been made to organize or extrapolate these models into broader theories. The Theory of Ecology brings together some of the most respected and creative theoretical ecologists of this era to advance a comprehensive, conceptual articulation of ecological theories. The contributors cover a wide range of topics, from ecological niche theory to population dynamic theory to island biogeography theory. Collectively, the chapters ably demonstrate how theory in ecology accounts for observations about the natural world and how models provide predictive understandings. It organizes these models into constitutive domains that highlight the strengths and weaknesses of ecological understanding. This book is a milestone in ecological theory and is certain to motivate future empirical and theoretical work in one of the most exciting and active domains of the life sciences.
Author: David Ellerman Publisher: Springer Nature ISBN: 3030865525 Category : Philosophy Languages : en Pages : 121
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: Daniel Hershey Publisher: World Scientific ISBN: 1908978651 Category : Technology & Engineering Languages : en Pages : 275
Book Description
Entropy is a measure of order and disorder. If left alone, aging systems go spontaneously from youthful, low entropy and order to old, high entropy and disorder. This book presents the commonality of entropy principles which govern the birth, maturation, and senescent history of aging humans, corporations, and the universe. Mainly we introduce an entropy theory of aging, based on the non-equilibrium thermodynamic ideas of Ilya Prigogine, leading to the thermodynamic concepts of Excess Entropy (EE) and Excess Entropy Production (EEP). We describe the aging process in humans in terms of the EE and EEP concepts. This book also describes the informational entropy theory and equations of Claude Shannon and the six Hershey parameters which trace and mark the lifecycle of corporations. To conclude, this volume uses classical and informational entropy concepts, equations and calculations to explain the birth, evolution, and death of our aging universe, and all of this in relation to the concept of Infinity./a
Author: John Harte Publisher: OUP Oxford ISBN: 0191621161 Category : Science Languages : en Pages : 282
Book Description
This pioneering graduate textbook provides readers with the concepts and practical tools required to understand the maximum entropy principle, and apply it to an understanding of ecological patterns. Rather than building and combining mechanistic models of ecosystems, the approach is grounded in information theory and the logic of inference. Paralleling the derivation of thermodynamics from the maximum entropy principle, the state variable theory of ecology developed in this book predicts realistic forms for all metrics of ecology that describe patterns in the distribution, abundance, and energetics of species over multiple spatial scales, a wide range of habitats, and diverse taxonomic groups. The first part of the book is foundational, discussing the nature of theory, the relationship of ecology to other sciences, and the concept of the logic of inference. Subsequent sections present the fundamentals of macroecology and of maximum information entropy, starting from first principles. The core of the book integrates these fundamental principles, leading to the derivation and testing of the predictions of the maximum entropy theory of ecology (METE). A final section broadens the book's perspective by showing how METE can help clarify several major issues in conservation biology, placing it in context with other theories and highlighting avenues for future research.
Author: Kofi Kissi Dompere
Author: Kofi Kissi Dompere
Author: Kenneth D. Bailey
Author: Robert M. Gray
Author: Nathaniel F. G. Martin
Author: Arieh Ben-naim
Author: Joseph Ellis Trevor
Author: Samuel M. Scheiner
Author: David Ellerman
Author: Daniel Hershey
Author: John Harte