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[电子工程] Uncertainty and Information:Foundations of Generalized Information Theory

Uncertainty and Information:Foundations of Generalized Information Theory

Uncertainty and Information:Foundations of Generalized Information Theory, Wiley Pub.

book 收藏 
 作者 George J. Klir
 ISBN 0-471-74867-6
 出版日期/版本 2006
 格式 PDF Adobe Acrobat

主题内容

The principal aim of this book is to provide the reader with a comprehensive and in-depth overview of the two-dimensional framework by which the research in GIT has been guided, and to present the main results that have been obtained by this research. Also covered are the main features of two classical information theories.One of them, covered in Chapter 3, is based on the concept of probability.This classical theory is well known and is extensively covered in the literature. The other one, covered in Chapter 2, is based on the dual concepts of possibility and necessity. This classical theory is older and more fundamental, but it is considerably less visible and has often been incorrectly dismissed in the literature as a special case of the probability-based information theory. These two classical information theories, which are formally incomparable, are the roots from which distinct generalizations are obtained. Principal results regarding generalized uncertainty theories that are based on classical set theory are covered in Chapters 4–6.While the focus in Chapter 4 is on the common properties of uncertainty representation in all these theories, Chapter 5 is concerned with special properties of individual uncertainty theories.The issue of how to measure the amount of uncertainty (and the associated information) in situations formalized in the various uncertainty theories is thoroughly investigated in Chapter 6. Chapter 7 presents a concise introduction to the fundamentals of fuzzy set theory, and the fuzzification of uncertainty theories is discussed in Chapter 8, in both general and specific terms. Methodological issues associated with GIT are discussed in Chapter 9. Finally, results and open problems emerging from GIT are summarized and assessed in Chapter 10. The book can be used in several ways and, due to the universal applicability of GIT, it is relevant to professionals in virtually any area of human affairs. While it is written primarily as a textbook for a one-semester graduate course, its utility extends beyond the classroom environment. Due to the comprehensive and coherent presentation of the subject and coverage of some previously unpublished results, the book is also a useful resource for researchers. Although the treatment of uncertainty and information in the book is mathematical, the required mathematical background is rather modest: the reader is only required to be familiar with the fundamentals of classical set theory, probability theory and the calculus. Otherwise, the book is completely selfcontained, and it is thus suitable for self-study. While working on the book, clarity of presentation was always on my mind. To achieve it, I use examples and visual illustrations copiously. Each chapter is also accompanied by an adequate number of exercises, which allow readers to test their understanding of the studied material.The main text is only rarely interrupted by bibliographical, historical, or any other references. Almost all references are covered in specific Notes, organized by individual topics and located at the end of each chapter.These notes contain ample information for further study. For many years, I have been pursuing research on GIT while, at the same time, teaching an advanced graduate course in this area to systems science students at Binghamton University in New York State (SUNY-Binghamton).Due to rapid developments in GIT, I have had to change the content of the course each year to cover the emerging new results. This book is based, at least to some degree, on the class notes that have evolved for this course over the years. Some parts of the book, especially in Chapters 6 and 9, are based on my own research. It is my hope that this book will establish a better understanding of the very complex concepts of information-based uncertainty and uncertainty-based information, and that it will stimulate further research and education in the important and rapidly growing area of generalized information theory.
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