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Theory of Information and its Value
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. Strat...
Nonlinear Nonequilibrium Thermodynamics II
This two-volume work gives the first detailed coherent treatment of a relatively young branch of statistical physics - nonlinear nonequilibrium and fluctuational dissipative thermodynamics. This area of research has taken shape rather recently: its de~elopment began in 1959. The earlier theory - linear nonequilibrium ther modynamics - is in principle a simple special case of the new theory. Despite the fact that the title of the book includes the word 'nonlinear', it also covers the results of linear nonequilibrium thermodynamics. The presentation of the linear and nonlinear theories is done within a common theoretical framework that is not subject to the linearity condition. The author hope...
Nonlinear Nonequilibrium Thermodynamics I
This book gives the first detailed coherent treatment of a relatively young branch of statistical physics - nonlinear nonequilibrium and fluctuation-dissipative thermo dynamics. This area of research has taken shape fairly recently: its development began in 1959. The earlier theory -linear nonequilibrium thermodynamics - is in principle a simple special case of the new theory. Despite the fact that the title of this book includes the word "nonlinear", it also covers the results of linear nonequilibrium thermodynamics. The presentation of the linear and nonlinear theories is done within a common theoretical framework that is not subject to the linearity condition. The author hopes that the re...
Quantum Statistics of Dense Gases and Nonideal Plasmas
The aim of this book is the pedagogical exploration of the basic principles of quantum-statistical thermodynamics as applied to various states of matter – ranging from rare gases to astrophysical matter with high-energy density. The reader will learn in this work that thermodynamics and quantum statistics are still the concepts on which even the most advanced research is operating - despite of a flood of modern concepts, classical entities like temperature, pressure, energy and entropy are shown to remain fundamental. The physics of gases, plasmas and high-energy density matter is still a growing field and even though solids and liquids dominate our daily life, more than 99 percent of the visible Universe is in the state of gases and plasmas and the overwhelming part of matter exists at extreme conditions connected with very large energy densities, such as in the interior of stars. This text, combining material from lectures and advanced seminars given by the authors over many decades, is a must-have introduction and reference for both newcomers and seasoned researchers alike.
Kalman Filtering
This book provides readers with a solid introduction to the theoretical and practical aspects of Kalman filtering. It has been updated with the latest developments in the implementation and application of Kalman filtering, including adaptations for nonlinear filtering, more robust smoothing methods, and developing applications in navigation. All software is provided in MATLAB, giving readers the opportunity to discover how the Kalman filter works in action and to consider the practical arithmetic needed to preserve the accuracy of results. Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department -- to obtain the manual, send an email to ialine@wiley.com.
Nonequilibrium Statistical Physics
A comprehensive and pedagogical text on nonequilibrium statistical physics, covering topics from random walks to pattern formation.
Physics of Self-Organization and Evolution
This thoroughly updated version of the German authoritative work on self-organization has been completely rewritten by internationally renowned experts and experienced book authors to also include a review of more recent literature. It retains the original enthusiasm and fascination surrounding thermodynamic systems far from equilibrium, synergetics, and the origin of life, representing an easily readable book and tutorial on this exciting field. The book is unique in covering in detail the experimental and theoretical fundamentals of self-organizing systems as well as such selected features as random processes, structural networks and multistable systems, while focusing on the physical and theoretical modeling of natural selection and evolution processes. The authors take examples from physics, chemistry, biology and social systems, and include results hitherto unpublished in English. The result is a one-stop resource relevant for students and scientists in physics or related interdisciplinary fields, including mathematical physics, biophysics, information science and nanotechnology.
Extended Kalman Filter
1: Extended Kalman filter: Introduces the extended Kalman filter (EKF), a core tool in nonlinear estimation. 2: Bra–ket notation: Explains the mathematical foundation, focusing on the structure of quantumlike systems. 3: Curvature: Discusses the concept of curvature and its influence on the performance of nonlinear filters. 4: Maximum likelihood estimation: Details the statistical approach used for estimating parameters with the highest likelihood. 5: Kalman filter: Provides an indepth exploration of the Kalman filter, the basis for many state estimation techniques. 6: Covariance matrix: Describes the covariance matrix and its role in quantifying uncertainty in filtering. 7: Propagation of...
Tracking and Sensor Data Fusion
Sensor Data Fusion is the process of combining incomplete and imperfect pieces of mutually complementary sensor information in such a way that a better understanding of an underlying real-world phenomenon is achieved. Typically, this insight is either unobtainable otherwise or a fusion result exceeds what can be produced from a single sensor output in accuracy, reliability, or cost. This book provides an introduction Sensor Data Fusion, as an information technology as well as a branch of engineering science and informatics. Part I presents a coherent methodological framework, thus providing the prerequisites for discussing selected applications in Part II of the book. The presentation mirror...
Algorithms and Law
Exploring issues from big-data to robotics, this volume is the first to comprehensively examine the regulatory implications of AI technology.
