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Dynamics of Information Systems: Mathematical Foundations

Author : Alexey Sorokin

Publisher : Springer Science & Business Media

Page : 374 pages

File Size : 17,20 MB

Release : 2012-08-04

Category : Business & Economics

ISBN : 146143906X

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Book Description

This book presents recent developments and results found by participants of the Third International Conference on the Dynamics of Information Systems, which took place at the University of Florida, Gainesville FL, USA on February 16-18, 2011. The purpose of this conference was to bring together scientists and engineers from industry, government, and universities to exchange knowledge and results in a broad range of topics relevant to the theory and practice of the dynamics of information systems. Dynamics of Information plays an increasingly critical role in our society. The influence of information on social, biological, genetic, and military systems must be better understood to achieve large advances in the capability and understanding of these systems. Applications are widespread and include: research in evolutionary theory, optimization of information workflow, military applications, climate networks, collision work, and much more. Dynamics of Information plays an increasingly critical role in our society. The influence of information on social, biological, genetic, and military systems must be better understood to achieve large advances in the capability and understanding of these systems. Applications are widespread and include: research in evolutionary theory, optimization of information workflow, military applications, climate networks, collision work, and much more.



Foundations of Complex Systems

Author : G. Nicolis

Publisher : World Scientific

Page : 343 pages

File Size : 22,71 MB

Release : 2007

Category : Mathematics

ISBN : 9812700439

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Book Description

Complexity is emerging as a post-Newtonian paradigm for approaching a large body of phenomena of concern at the crossroads of physical, engineering, environmental, life and human sciences from a unifying point of view. This book outlines the foundations of modern complexity research as it arose from the cross-fertilization of ideas and tools from nonlinear science, statistical physics and numerical simulation. It is shown how these developments lead to an understanding, both qualitative and quantitative, of the complex systems encountered in nature and in everyday experience and, conversely, how natural complexity acts as a source of inspiration for progress at the fundamental level.



Mathematical Foundations of Quantum Information and Computation and Its Applications to Nano- and Bio-systems

Author : Masanori Ohya

Publisher : Springer Science & Business Media

Page : 768 pages

File Size : 21,25 MB

Release : 2011-01-15

Category : Science

ISBN : 9400701713

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Book Description

This monograph provides a mathematical foundation to the theory of quantum information and computation, with applications to various open systems including nano and bio systems. It includes introductory material on algorithm, functional analysis, probability theory, information theory, quantum mechanics and quantum field theory. Apart from standard material on quantum information like quantum algorithm and teleportation, the authors discuss findings on the theory of entropy in C*-dynamical systems, space-time dependence of quantum entangled states, entangling operators, adaptive dynamics, relativistic quantum information, and a new paradigm for quantum computation beyond the usual quantum Turing machine. Also, some important applications of information theory to genetics and life sciences, as well as recent experimental and theoretical discoveries in quantum photosynthesis are described.



The Dynamics and Evolution of Social Systems

Author : Jürgen Klüver

Publisher : Springer Science & Business Media

Page : 308 pages

File Size : 45,23 MB

Release : 2000-07-31

Category : Business & Economics

ISBN : 9780792364436

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Book Description

The central topic of this book is the mathematical analysis of social systems, understood in the following rather classical way: social systems consist of social actors who interact according to specific rules of interactions; the dynamics of social systems is then the consequences of these interactions, viz., the self-organization of social systems. According to particular demands of their environment, social systems are able to behave in an adaptive manner, that is they can change their rules of interaction by certain meta rules and thus generate a meta dynamics. It is possible to model and analyse mathematically both dynamics and meta dynamics, using cellular automata and genetic algorithms. These tools allow social systems theory to be carried through as precisely as the theories of natural systems, a feat that has not previously been possible. Readership: Researchers and graduate students in the fields of theoretical sociology and social and general systems theory and other interested scientists. No specialised knowledge of mathematics and/or computer science is required.



Mathematical Foundations of Computer Networking

Author : Srinivasan Keshav

Publisher : Pearson Education

Page : 496 pages

File Size : 46,58 MB

Release : 2012

Category : Computers

ISBN : 0321792106

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Book Description

Mathematical techniques pervade current research in computer networking, yet are not taught to most computer science undergraduates. This self-contained, highly-accessible book bridges the gap, providing the mathematical grounding students and professionals need to successfully design or evaluate networking systems. The only book of its kind, it brings together information previously scattered amongst multiple texts. It first provides crucial background in basic mathematical tools, and then illuminates the specific theories that underlie computer networking. Coverage includes: * Basic probability * Statistics * Linear Algebra * Optimization * Signals, Systems, and Transforms, including Fourier series and transforms, Laplace transforms, DFT, FFT, and Z transforms * Queuing theory * Game Theory * Control theory * Information theory



Foundations of Data Science

Author : Avrim Blum

Publisher : Cambridge University Press

Page : 433 pages

File Size : 19,62 MB

Release : 2020-01-23

Category : Computers

ISBN : 1108617360

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Book Description

This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data.



Mathematics of Big Data

Author : Jeremy Kepner

Publisher : MIT Press

Page : 443 pages

File Size : 27,78 MB

Release : 2018-08-07

Category : Computers

ISBN : 0262347911

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Book Description

The first book to present the common mathematical foundations of big data analysis across a range of applications and technologies. Today, the volume, velocity, and variety of data are increasing rapidly across a range of fields, including Internet search, healthcare, finance, social media, wireless devices, and cybersecurity. Indeed, these data are growing at a rate beyond our capacity to analyze them. The tools—including spreadsheets, databases, matrices, and graphs—developed to address this challenge all reflect the need to store and operate on data as whole sets rather than as individual elements. This book presents the common mathematical foundations of these data sets that apply across many applications and technologies. Associative arrays unify and simplify data, allowing readers to look past the differences among the various tools and leverage their mathematical similarities in order to solve the hardest big data challenges. The book first introduces the concept of the associative array in practical terms, presents the associative array manipulation system D4M (Dynamic Distributed Dimensional Data Model), and describes the application of associative arrays to graph analysis and machine learning. It provides a mathematically rigorous definition of associative arrays and describes the properties of associative arrays that arise from this definition. Finally, the book shows how concepts of linearity can be extended to encompass associative arrays. Mathematics of Big Data can be used as a textbook or reference by engineers, scientists, mathematicians, computer scientists, and software engineers who analyze big data.



Dynamics Of Complex Systems

Author : Yaneer Bar-yam

Publisher : CRC Press

Page : 866 pages

File Size : 43,93 MB

Release : 2019-03-04

Category : Mathematics

ISBN : 0429717598

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Book Description

This book aims to develop models and modeling techniques that are useful when applied to all complex systems. It adopts both analytic tools and computer simulation. The book is intended for students and researchers with a variety of backgrounds.



Variation Principle in Informational Macrodynamics

Author : Vladimir S. Lerner

Publisher : Springer Science & Business Media

Page : 278 pages

File Size : 20,53 MB

Release : 2012-12-06

Category : Computers

ISBN : 1461504015

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Book Description

Information Macrodynamics (IMD) belong to an interdisciplinary science that represents a new theoretical and computer-based methodology for a system informational descriptionand improvement,including various activities in such areas as thinking, intelligent processes, communications, management, and other nonphysical subjects with their mutual interactions, informational superimposition, and theinformation transferredbetweeninteractions. The IMD is based on the implementation of a single concept by a unique mathematical principle and formalism, rather than on an artificial combination of many arbitrary, auxiliary concepts and/or postulates and different mathematical subjects, such as the game, automata, catastrophe, logical operations theories, etc. This concept is explored mathematically using classical mathematics as calculus of variation and the probability theory, which are potent enough, without needing to developnew,specifiedmathematical systemicmethods. The formal IMD model automatically includes the related results from other fields, such as linear, nonlinear, collective and chaotic dynamics, stability theory, theory of information, physical analogies of classical and quantum mechanics, irreversible thermodynamics, andkinetics. The main IMD goal is to reveal the information regularities, mathematically expressed by the considered variation principle (VP), as a mathematical tool to extractthe regularities and define the model, whichdescribes theregularities. The IMD regularities and mechanisms are the results of the analytical solutions and are not retained by logical argumentation, rational introduction, and a reasonable discussion. The IMD's information computer modeling formalism includes a human being (as an observer, carrier and producer ofinformation), with a restoration of the model during the objectobservations.



Information Systems Analysis and Modeling

Author : Vladimir S. Lerner

Publisher : Springer Science & Business Media

Page : 329 pages

File Size : 45,13 MB

Release : 2012-12-06

Category : Computers

ISBN : 1461546397

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Book Description

Informational Macrodynamics (IMD) presents the unified information systemic approach with common information language for modeling, analysis and optimization of a variety of interactive processes, such as physical, biological, economical, social, and informational, including human activities. Comparing it with thermodynamics, which deals with transformation energy and represents a theoretical foundation of physical technology, IMD deals with transformation information, and can be considered a theoretical foundation of Information Computer Technology (ICT). ICT includes but is not limited to applied computer science, computer information systems, computer and data communications, software engineering, and artificial intelligence. In ICT, information flows from different data sources, and interacts to create new information products. The information flows may interact physically or via their virtual connections, initiating an information dynamic process that can be distributed in space. As in physics, a problem is understanding general regularities of the information processes in terms of information law, for the engineering and technological design, control, optimization, and development of computer technology, operations, manipulations, and management of real information objects. Information Systems Analysis and Modeling: An Informational Macrodynamics Approach belongs to an interdisciplinary science that represents the new theoretical and computer-based methodology for system informational description and improvement, including various activities in such interdisciplinary areas as thinking, intelligent processes, management, and other nonphysical subjects with their mutual interactions, informational superimpositions, and the information transferred between interactions. Information Systems Analysis and Modeling: An Informational Macrodynamics Approach can be used as a textbook or secondary text in courses on computer science, engineering, business, management, education, and psychology and as a reference for research and industry.