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Books > Reference & Interdisciplinary > Communication studies > Information theory
This multidisciplinary volume is the second in the STEAM-H series to feature invited contributions on mathematical applications in naval engineering. Seeking a more holistic approach that transcends current scientific boundaries, leading experts present interdisciplinary instruments and models on a broad range of topics. Each chapter places special emphasis on important methods, research directions, and applications of analysis within the field. Fundamental scientific and mathematical concepts are applied to topics such as microlattice materials in structural dynamics, acoustic transmission in low Mach number liquid flow, differential cavity ventilation on a symmetric airfoil, Kalman smoother, metallic foam metamaterials for vibration damping and isolation, seal whiskers as a bio-inspired model for the reduction of vortex-induced vibrations, multidimensional integral for multivariate weighted generalized Gaussian distributions, minimum uniform search track placement for rectangular regions, antennas in the maritime environment, the destabilizing impact of non-performers in multi-agent groups, inertial navigation accuracy with bias modeling. Carefully peer-reviewed and pedagogically presented for a broad readership, this volume is perfect to graduate and postdoctoral students interested in interdisciplinary research. Researchers in applied mathematics and sciences will find this book an important resource on the latest developments in naval engineering. In keeping with the ideals of the STEAM-H series, this volume will certainly inspire interdisciplinary understanding and collaboration.
Introduction to the Theory of Quantum Information Processing provides the material for a one-semester graduate level course on quantum information theory and quantum computing for students who have had a one-year graduate course in quantum mechanics. Many standard subjects are treated, such as density matrices, entanglement, quantum maps, quantum cryptography, and quantum codes. Also included are discussions of quantum machines and quantum walks. In addition, the book provides detailed treatments of several underlying fundamental principles of quantum theory, such as quantum measurements, the no-cloning and no-signaling theorems, and their consequences. Problems of various levels of difficulty supplement the text, with the most challenging problems bringing the reader to the forefront of active research. This book provides a compact introduction to the fascinating and rapidly evolving interdisciplinary field of quantum information theory, and it prepares the reader for doing active research in this area.
How do we design a self-organizing system? Is it possible to validate and control non-deterministic dynamics? What is the right balance between the emergent patterns that bring robustness, adaptability and scalability, and the traditional need for verification and validation of the outcomes? The last several decades have seen much progress from original ideas of "emergent functionality" and "design for emergence", to sophisticated mathematical formalisms of "guided self-organization". And yet the main challenge remains, attracting the best scientific and engineering expertise to this elusive problem. This book presents state-of-the-practice of successfully engineered self-organizing systems, and examines ways to balance design and self-organization in the context of applications. As demonstrated in this second edition of Advances in Applied Self-Organizing Systems, finding this balance helps to deal with practical challenges as diverse as navigation of microscopic robots within blood vessels, self-monitoring aerospace vehicles, collective and modular robotics adapted for autonomous reconnaissance and surveillance, self-managing grids and multiprocessor scheduling, data visualization and self-modifying digital and analog circuitry, intrusion detection in computer networks, reconstruction of hydro-physical fields, traffic management, immunocomputing and nature-inspired computation. Many algorithms proposed and discussed in this volume are biologically inspired, and the reader will also gain an insight into cellular automata, genetic algorithms, artificial immune systems, snake-like locomotion, ant foraging, birds flocking, neuromorphic circuits, amongst others. Demonstrating the practical relevance and applicability of self-organization, Advances in Applied Self-Organizing Systems will be an invaluable tool for advanced students and researchers in a wide range of fields.
This book provides the mathematical foundations of networks of linear control systems, developed from an algebraic systems theory perspective. This includes a thorough treatment of questions of controllability, observability, realization theory, as well as feedback control and observer theory. The potential of networks for linear systems in controlling large-scale networks of interconnected dynamical systems could provide insight into a diversity of scientific and technological disciplines. The scope of the book is quite extensive, ranging from introductory material to advanced topics of current research, making it a suitable reference for graduate students and researchers in the field of networks of linear systems. Part I can be used as the basis for a first course in Algebraic System Theory, while Part II serves for a second, advanced, course on linear systems. Finally, Part III, which is largely independent of the previous parts, is ideally suited for advanced research seminars aimed at preparing graduate students for independent research. "Mathematics of Networks of Linear Systems" contains a large number of exercises and examples throughout the text making it suitable for graduate courses in the area.
This treatment of modern topics related to the control of nonlinear systems is a collection of contributions celebrating the work of Professor Henk Nijmeijer and honoring his 60th birthday. It addresses several topics that have been the core of Professor Nijmeijer's work, namely: the control of nonlinear systems, geometric control theory, synchronization, coordinated control, convergent systems and the control of underactuated systems. The book presents recent advances in these areas, contributed by leading international researchers in systems and control. In addition to the theoretical questions treated in the text, particular attention is paid to a number of applications including (mobile) robotics, marine vehicles, neural dynamics and mechanical systems generally. This volume provides a broad picture of the analysis and control of nonlinear systems for scientists and engineers with an interest in the interdisciplinary field of systems and control theory. The reader will benefit from the expert participants' ideas on important open problems with contributions that represent the state of the art in nonlinear control.
This book focuses on systems engineering, systems thinking, and how that thinking can be learned in practice. It describes a novel analytical framework based on activity theory for understanding how systems thinking evolves and how it can be improved to support multidisciplinary teamwork in the context of system development and systems engineering. This method, developed using data collected over four years from three different small space systems engineering organizations, can be applied in a wide variety of work activities in the context of engineering design and beyond in order to monitor and analyze multidisciplinary interactions in working teams over time. In addition, the book presents a practical strategy called WAVES (Work Activity for a Evolution of Systems engineering and thinking), which fosters the practical learning of systems thinking with the aim of improving process development in different industries. The book offers an excellent resource for researchers and practitioners interested in systems thinking and in solutions to support its evolution. Beyond its contribution to a better understanding of systems engineering, systems thinking and how it can be learned in real-world contexts, it also introduce a suitable analysis framework that helps to bridge the gap between the latest social science research and engineering research.
First published in 1958, John von Neumann's classic work The Computer and the Brain explored the analogies between computing machines and the living human brain. Von Neumann showed that the brain operates both digitally and analogically, but also has its own unique statistical language. And more than fifty years after its inception the von Neumann architecture - an organizational framework for computer design - still lies at the heart of today's machines. In his foreword to this new edition, Ray Kurzweil, a futurist famous for his own musings on the relationship between technology and consciousness, places von Neumann's work in a historical context and shows how it remains relevant today.
This volume presents selected aspects of non-integer, or fractional order systems, whose analysis, synthesis and applications have increasingly become a real challenge for various research communities, ranging from science to engineering. The spectrum of applications of the fractional order calculus has incredibly expanded, in fact it would be hard to find a science/engineering-related subject area where the fractional calculus had not been incorporated. The content of the fractional calculus is ranged from pure mathematics to engineering implementations and so is the content of this volume. The volume is subdivided into six parts, reflecting particular aspects of the fractional order calculus. The first part contains a single invited paper on a new formulation of fractional-order descriptor observers for fractional-order descriptor continous LTI systems. The second part provides new elements to the mathematical theory of fractional-order systems. In the third part of this volume, a bunch of new results in approximation, modeling and simulations of fractional-order systems is given. The fourth part presents new solutions to some problems in controllability and control of non-integer order systems, in particular fractional PID-like control. The fifth part analyzes the stability of non-integer order systems and some new results are offered in this important respect, in particular for discrete-time systems. The final, sixth part of this volume presents a spectrum of applications of the noninteger order calculus, ranging from bi-fractional filtering, in particular of electromyographic signals, through the thermal diffusion and advection diffusion processes to the SIEMENS platform implementation. This volume's papers were all subjected to stimulating comments and discussions from the active audience of the RRNR'2014, the 6th Conference on Non-integer Order Calculus and Its Applications that was organized by the Department of Electrical, Control and Computer Engineering, Opole University of Technology, Opole, Poland.
The competitiveness of firms, regions and countries greatly depends on the generation, dissemination and application of new knowledge. Modern innovation research is challenged by the need to incorporate knowledge generation and dissemination processes into the analysis so as to disentangle the complexity of these dynamic processes. With innovation, however, strong uncertainty, nonlinearities and actor heterogeneity become central factors that are at odds with traditional modeling techniques anchored in equilibrium and homogeneity. This text introduces SKIN (Simulation Knowledge Dynamics in Innovation Networks), an agent-based simulation model that primarily focuses on joint knowledge creation and exchange of knowledge in innovation co-operations and networks. In this context, knowledge is explicitly modeled and not approximated by, for instance, the level of accumulated R&D investment. The SKIN approach supports applications in different domains ranging from sector-based research activities in knowledge-intensive industries to the activities of international research consortia engaged in basic and applied research. Following a general description of the SKIN model, several applications and modifications are presented. Each chapter introduces in detail the structure of the model, the relevant methodological considerations and the analysis of simulation results, while options for empirically validating the models' structure and outcomes are also discussed. The book considers the scope of further applications and outlines prospects for the development of joint modeling strategies.
Hyperbolic geometry is an essential part of theoretical astrophysics and cosmology. Besides specialists of these domains, many specialists of new domains start to show a growing interest both to hyperbolic geometry and to cellular automata. This is especially the case in biology and computer science. This book gives the reader a deep and efficient introduction to an algorithmic approach to hyperbolic geometry. It focuses the attention on the possibilities to obtain in this frame the power of computing everything a computer can compute, that is to say: universality. The minimal ways to get universality are investigated in a large family of tilings of the hyperbolic plane. In several cases the best results are obtained.In all cases, the results are close to the theoretical best values. This gives rise to fantastic illustrations: the results are jewels in all meanings of the word. ------------------------ Maurice MARGENSTERN is professor emeritus at the University of Lorraine, he is a member of LITA, the research unit of computer science in the campus of Metz of this university. Professor Margenstern is amongst top world experts in theory of computation, mathematical machines and geometry. He is a pioneer in cellular automata in hyperbolic spaces.
The book is a collection of peer-reviewed scientific papers submitted by active researchers in the 36th National System Conference (NSC 2012). NSC is an annual event of the Systems Society of India (SSI), primarily oriented to strengthen the systems movement and its applications for the welfare of humanity. A galaxy of academicians, professionals, scientists, statesman and researchers from different parts of the country and abroad are invited to attend the Conference. The book presents various research articles in the area of system modelling in all disciplines of engineering sciences as well as socio-economic systems. The book can be used as a tool for further research.
These proceedings present the results of the Eleventh International Conference on Dependability and Complex Systems DepCoS-RELCOMEX which took place in a picturesque Brunow Palace in Poland from 27th June to 1st July, 2016. DepCoS-RELCOMEX is a series of international conferences organized annually by Department of Computer Engineering of Wroclaw University of Science and Technology since 2006. The roots of the series go as far back as to the seventies of the previous century - the first RELCOMEX conference took place in 1977 - and now its main aim is to promote a multi-disciplinary approach to dependability problems in theory and engineering practice of complex systems. Complex systems, nowadays most often computer-based and distributed, are built upon a variety of technical, information, software and human resources. The challenges in their design, analysis and maintenance not only originate from the involved technical and organizational structures but also from the complexity of the information processes that must be efficiently executed in a diverse, often hostile operational environment. Traditional methods of reliability evaluation focused only on technical resources are usually insufficient in this context and more innovative, multidisciplinary methods of dependability analysis must be applied. The diversity of the topics which need to be considered is well illustrated by the selection of the submissions in these proceedings with their subjects ranging from mathematical models and design methodologies through software engineering and data security issues up to practical problems in technical, e.g. transportation, systems.
This book presents the details of the BONUS algorithm and its real world applications in areas like sensor placement in large scale drinking water networks, sensor placement in advanced power systems, water management in power systems, and capacity expansion of energy systems. A generalized method for stochastic nonlinear programming based on a sampling based approach for uncertainty analysis and statistical reweighting to obtain probability information is demonstrated in this book. Stochastic optimization problems are difficult to solve since they involve dealing with optimization and uncertainty loops. There are two fundamental approaches used to solve such problems. The first being the decomposition techniques and the second method identifies problem specific structures and transforms the problem into a deterministic nonlinear programming problem. These techniques have significant limitations on either the objective function type or the underlying distributions for the uncertain variables. Moreover, these methods assume that there are a small number of scenarios to be evaluated for calculation of the probabilistic objective function and constraints. This book begins to tackle these issues by describing a generalized method for stochastic nonlinear programming problems. This title is best suited for practitioners, researchers and students in engineering, operations research, and management science who desire a complete understanding of the BONUS algorithm and its applications to the real world.
This SpringerBrief gives the reader a detailed account of how cybersecurity in Israel has evolved over the past two decades. The formation of the regions cybersecurity strategy is explored and an in-depth analysis of key developments in cybersecurity policy is provided. The authors examine cybersecurity from an integrative national perspective and see it as a set of policies and actions with two interconnected goals: to mitigate security risks and increase resilience and leverage opportunities enabled by cyber-space. Chapters include an insight into the planning and implementation of the National Security Concept strategy which facilitated the Critical Infrastructure Protection (CIP) agreement in 2002, (one of the first of its kind), the foundation of the Israeli Cyber-strategy in 2011, and details of the current steps being taken to establish a National Cyber Security Authority (NCSA). Cybersecurity in Israel will be essential reading for anybody interested in cyber-security policy, including students, researchers, analysts and policy makers alike.
A unified methodology for categorizing various complex objects is presented in this book. Through probability theory, novel asymptotically minimax criteria suitable for practical applications in imaging and data analysis are examined including the special cases such as the Jensen-Shannon divergence and the probabilistic neural network. An optimal approximate nearest neighbor search algorithm, which allows faster classification of databases is featured. Rough set theory, sequential analysis and granular computing are used to improve performance of the hierarchical classifiers. Practical examples in face identification (including deep neural networks), isolated commands recognition in voice control system and classification of visemes captured by the Kinect depth camera are included. This approach creates fast and accurate search procedures by using exact probability densities of applied dissimilarity measures. This book can be used as a guide for independent study and as supplementary material for a technically oriented graduate course in intelligent systems and data mining. Students and researchers interested in the theoretical and practical aspects of intelligent classification systems will find answers to: - Why conventional implementation of the naive Bayesian approach does not work well in image classification? - How to deal with insufficient performance of hierarchical classification systems? - Is it possible to prevent an exhaustive search of the nearest neighbor in a database?
It has been widely recognized nowadays the importance of introducing mathematical models that take into account possible sudden changes in the dynamical behavior of a high-integrity systems or a safety-critical system. Such systems can be found in aircraft control, nuclear power stations, robotic manipulator systems, integrated communication networks and large-scale flexible structures for space stations, and are inherently vulnerable to abrupt changes in their structures caused by component or interconnection failures. In this regard, a particularly interesting class of models is the so-called Markov jump linear systems (MJLS), which have been used in numerous applications including robotics, economics and wireless communication. Combining probability and operator theory, the present volume provides a unified and rigorous treatment of recent results in control theory of continuous-time MJLS. This unique approach is of great interest to experts working in the field of linear systems with Markovian jump parameters or in stochastic control. The volume focuses on one of the few cases of stochastic control problems with an actual explicit solution and offers material well-suited to coursework, introducing students to an interesting and active research area. The book is addressed to researchers working in control and signal processing engineering. Prerequisites include a solid background in classical linear control theory, basic familiarity with continuous-time Markov chains and probability theory, and some elementary knowledge of operator theory.
There are many methods of stable controller design for nonlinear systems. In seeking to go beyond the minimum requirement of stability, Adaptive Dynamic Programming in Discrete Time approaches the challenging topic of optimal control for nonlinear systems using the tools of adaptive dynamic programming (ADP). The range of systems treated is extensive; affine, switched, singularly perturbed and time-delay nonlinear systems are discussed as are the uses of neural networks and techniques of value and policy iteration. The text features three main aspects of ADP in which the methods proposed for stabilization and for tracking and games benefit from the incorporation of optimal control methods: * infinite-horizon control for which the difficulty of solving partial differential Hamilton-Jacobi-Bellman equations directly is overcome, and proof provided that the iterative value function updating sequence converges to the infimum of all the value functions obtained by admissible control law sequences; * finite-horizon control, implemented in discrete-time nonlinear systems showing the reader how to obtain suboptimal control solutions within a fixed number of control steps and with results more easily applied in real systems than those usually gained from infinite-horizon control; * nonlinear games for which a pair of mixed optimal policies are derived for solving games both when the saddle point does not exist, and, when it does, avoiding the existence conditions of the saddle point. Non-zero-sum games are studied in the context of a single network scheme in which policies are obtained guaranteeing system stability and minimizing the individual performance function yielding a Nash equilibrium. In order to make the coverage suitable for the student as well as for the expert reader, Adaptive Dynamic Programming in Discrete Time: * establishes the fundamental theory involved clearly with each chapter devoted to a clearly identifiable control paradigm; * demonstrates convergence proofs of the ADP algorithms to deepen understanding of the derivation of stability and convergence with the iterative computational methods used; and * shows how ADP methods can be put to use both in simulation and in real applications. This text will be of considerable interest to researchers interested in optimal control and its applications in operations research, applied mathematics computational intelligence and engineering. Graduate students working in control and operations research will also find the ideas presented here to be a source of powerful methods for furthering their study.
This book, edited and authored by a closely collaborating network of social scientists and psychologists, recasts typical research topics in these fields into the language of nonlinear, dynamic and complex systems. The aim is to provide scientists with different backgrounds - physics, applied mathematics and computer sciences - with the opportunity to apply the tools of their trade to an altogether new range of possible applications. At the same time, this book will serve as a first reference for a new generation of social scientists and psychologists wishing to familiarize themselves with the new methodology and the "thinking in complexity".
This volume features key contributions from the International Conference on Pattern Recognition Applications and Methods, (ICPRAM 2012,) held in Vilamoura, Algarve, Portugal from February 6th-8th, 2012. The conference provided a major point of collaboration between researchers, engineers and practitioners in the areas of Pattern Recognition, both from theoretical and applied perspectives, with a focus on mathematical methodologies. Contributions describe applications of pattern recognition techniques to real-world problems, interdisciplinary research, and experimental and theoretical studies which yield new insights that provide key advances in the field. This book will be suitable for scientists and researchers in optimization, numerical methods, computer science, statistics and for differential geometers and mathematical physicists.
Today it appears that we understand more about the universe than about our interconnected socio-economic world. In order to uncover organizational structures and novel features in these systems, we present the first comprehensive complex systems analysis of real-world ownership networks. This effort lies at the interface between the realms of economics and the emerging field loosely referred to as complexity science. The structure of global economic power is reflected in the network of ownership ties of companies and the analysis of such ownership networks has possible implications for market competition and financial stability. Thus this work presents powerful new tools for the study of economic and corporate networks that are only just beginning to attract the attention of scholars.
The book of nature is written in the language of mathematics Galileo Galilei, 1623 Metrology strives to supervise the ?ow of the measurand's true values throughconsecutive,arbitrarilyinterlockingseriesofmeasurements.Tohi- light this feature the term traceability has been coined. Traceability is said to be achieved, given the true values of each of the physical quantities entering and leaving the measurement are localized by speci?ed measu- ment uncertainties. The classical Gaussian error calculus is known to be con?ned to the tre- ment of random errors. Hence, there is no distinction between the true value of a measurand on the one side and the expectation of the respective es- mator on the other. This became apparent not until metrologists considered the e?ect of so-called unknown systematic errors. Unknown systematic errors are time-constant quantities unknown with respect to magnitude and sign. While random errors are treated via distribution densities, unknown syst- atic errors can only be assessed via intervals of estimated lengths. Unknown systematic errors were, in fact, addressed and discussed by Gauss himself. Gauss, however, argued that it were up to the experimenter to eliminate their causes and free the measured values from their in?uence.
Optimization, simulation and control play an increasingly important role in science and industry. Because of their numerous applications in various disciplines, research in these areas is accelerating at a rapid pace. This volume brings together the latest developments in these areas of research as well as presents applications of these results to a wide range of real-world problems. The book is composed of invited contributions by experts from around the world who work to develop and apply new optimization, simulation and control techniques either at a theoretical level or in practice. Some key topics presented include: equilibrium problems, multi-objective optimization, variational inequalities, stochastic processes, numerical analysis, optimization in signal processing, and various other interdisciplinary applications. This volume can serve as a useful resource for researchers, practitioners, and advanced graduate students of mathematics and engineering working in research areas where results in optimization, simulation and control can be applied.
The mathematical theory of "open" dynamical systems is a creation of the twentieth century. Its humble beginnings focused on ideas of Laplace transforms applied to linear problems of automatic control and to the analysis and synthesis of electrical circuits. However during the second half of the century, it flowered into a field based on an array of sophisticated mathematical concepts and techniques from algebra, nonlinear analysis and differential geometry. The central notion is that of a dynamical system that exchanges matter, energy, or information with its surroundings, i.e. an "open" dynamical system. The mathema tization of this notion evolved considerably over the years. The early development centered around the input/output point of view and led to important results, particularly in controller design. Thinking about open systems as a "black box" that accepts stimuli and produces responses has had a wide influence also in areas outside engineering, for example in biology, psychology, and economics. In the early 1960's, especially through the work of Kalman, input/state/output models came in vogue. This model class accommodates very nicely the internal initial conditions that are essentially always present in a dynamical system. The introduction of input/state/output models led to a tempestuous development that made systems and control into a mature discipline with a wide range of concepts, results, algorithms, and applications.
These proceedings contain the papers presented at the Third International Conference and Exhibition on Engineering Software held at Imperial College, London during the period April 11th - 13th, 1983. I must thank again the authors who submitted the large numbers of papers which made selection a difficult task. The theme of the conference is the use and application of computers in engineering. Many abbreviations have been invented to describe the use of computers from CAD, CAM, CADMAT etc. but the term which best describes the scope of the conference is Computer Aided Engineering, CAE. The papers have been split into sections covering different application areas such as Mechanical Engineering, Civil Engineering. Other sections cover techniques such as Finite Elements, Boundary Elements and General Simu lation. An important session at the conference was the new field of engineering databases and as in past conferences the special sessions were devoted to microcomputers. R.A. ADEY (EDITOR) ENGINEERING SOFTWARE DESIGN 3 MENU INPUT GENERATING SYSTEM FOR THE FORTRAN PROGRAMS I. Kovacic Institute of Structural and Earthquake Engineering Department of Civil Engineering University "Edvard Kardelj" of Ljubljana, Yugoslavia INTRODUCTION Although fortran Is losing competition with the new languages it Is still very used programming language, especially in the technical software production. Technical tasks are not to be described by a lot of data usually, as in business applications.
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