A new discipline, Quantum Information Science, has emerged in the last two decades of the twentieth century at the intersection of Physics, Mathematics, and Computer Science. Quantum Information Processing is an application of Quantum Information Science which covers the transformation, storage, and transmission of quantum information; it represents a revolutionary approach to information processing. Classical and Quantum Information covers topics in quantum computing, quantum information theory, and quantum error correction, three important areas of quantum information processing. Quantum information theory and quantum error correction build on the scope, concepts, methodology, and techniques developed in the context of their close relatives, classical information theory and classical error correcting codes. - Presents recent results in quantum computing, quantum information theory, and quantum error correcting codes - Covers both classical and quantum information theory and error correcting codes - The last chapter of the book covers physical implementation of quantum information processing devices - Covers the mathematical formalism and the concepts in Quantum Mechanics critical for understanding the properties and the transformations of quantum information

Objective Information Theory (OIT) is proposed to represent and compute the information in a large-scale complex information system with big data in this monograph. To formally analyze, design, develop, and evaluate the information, OIT interprets the information from essential nature, measures the information from mathematical properties, and models the information from concept, logic, and physic. As the exemplified applications, Air Traffic Control System (ATCS) and Smart Court SoSs (System of Systems) are introduced for practical OITs. This Open Access book can be used as a technical reference book in the field of information science and also a reference textbook for senior students and graduate ones in related majors.

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

This book is offers a comprehensive overview of information theory and error control coding, using a different approach then in existed literature. The chapters are organized according to the Shannon system model, where one block affects the others. A relatively brief theoretical introduction is provided at the beginning of every chapter, including a few additional examples and explanations, but without any proofs. And a short overview of some aspects of abstract algebra is given at the end of the corresponding chapters. The characteristic complex examples with a lot of illustrations and tables are chosen to provide detailed insights into the nature of the problem. Some limiting cases are presented to illustrate the connections with the theoretical bounds. The numerical values are carefully selected to provide in-depth explanations of the described algorithms. Although the examples in the different chapters can be considered separately, they are mutually connected and the conclusions for one considered problem relate to the others in the book.

This book provides an up-to-date introduction to information theory. In addition to the classical topics discussed, it provides the first comprehensive treatment of the theory of I-Measure, network coding theory, Shannon and non-Shannon type information inequalities, and a relation between entropy and group theory. ITIP, a software package for proving information inequalities, is also included. With a large number of examples, illustrations, and original problems, this book is excellent as a textbook or reference book for a senior or graduate level course on the subject, as well as a reference for researchers in related fields.

Illustrates computers, control and information theory. Features Army High Performance Computing Research Center; U.S. Patent and Trademark Office; National Coordination Office for High Performance Computing and Communication with samples of research and the Blue Book; National Institute of Standards and Technology; Government Information and the Internet; National MetaCenter for Computational Science and Engineering; Clearinghouse for Networked Information Discovery and Retrieval (CNIDR); Advanced Computing Lab at Los Alamos National Laboratory; and more.

Failure-Tolerant Computer Design focuses on the use of redundancy theory in improving the reliability of computers. The book first offers information on redundancy theory and limit theorems. Discussions focus on applications in determining the optimum placement of restoring organs; time asymptotes for log failure probability for exponential survival probability; reliability of multiple-function system with paralleled individual units; and basic concepts for making reliable computers out of unreliable parts. The text then examines decision theory in redundant systems and adaptive decision elements. The publication examines the interconnection structure for redundant logic and redundant relay theory. Topics include Moore-Shannon limit theorem; systematic groupings of inputs in single-layer error-correcting interwoven redundant logic; interwoven logic with alternating-layer error correction; and interwoven logic with single-layer error correction. The book also elaborates on transition analyses in reliability theory, including Markov chain theory and probability bounds in Markov chains having many states or inexactly known transition matrices. The manuscript is a vital source of data for engineers and researchers interested in failure-tolerant computer design.