This book is the first to report on theoretical breakthroughs on control of complex dynamical systems developed by collaborative researchers in the two fields of dynamical systems theory and control theory. As well, its basic point of view is of three kinds of complexity: bifurcation phenomena subject to model uncertainty, complex behavior including periodic/quasi-periodic orbits as well as chaotic orbits, and network complexity emerging from dynamical interactions between subsystems. Analysis and Control of Complex Dynamical Systems offers a valuable resource for mathematicians, physicists, and biophysicists, as well as for researchers in nonlinear science and control engineering, allowing them to develop a better fundamental understanding of the analysis and control synthesis of such complex systems.

This book provides robust analysis and synthesis tools for Markovian jump systems in the finite-time domain with specified performances. It explores how these tools can make the systems more applicable to fields such as economic systems, ecological systems and solar thermal central receivers, by limiting system trajectories in the desired bound in a given time interval. Robust Control for Discrete-Time Markovian Jump Systems in the Finite-Time Domain focuses on multiple aspects of finite-time stability and control, including: finite-time H-infinity control; finite-time sliding mode control; finite-time multi-frequency control; finite-time model predictive control; and high-order moment finite-time control for multi-mode systems and also provides many methods and algorithms to solve problems related to Markovian jump systems with simulation examples that illustrate the design procedure and confirm the results of the methods proposed. The thorough discussion of these topics makes the book a useful guide for researchers, industrial engineers and graduate students alike, enabling them systematically to establish the modeling, analysis and synthesis for Markovian jump systems in the finite-time domain.

This book reports on the latest advances in the study of Networked Control Systems (NCSs). It highlights novel research concepts on NCSs; the analysis and synthesis of NCSs with special attention to their networked character; self- and event-triggered communication schemes for conserving limited network resources; and communication and control co-design for improving the efficiency of NCSs. The book will be of interest to university researchers, control and network engineers, and graduate students in the control engineering, communication and network sciences interested in learning the core principles, methods, algorithms and applications of NCSs.

This book discusses recent advances in the estimation and control of networked systems with unacknowledged packet losses: systems usually known as user-datagram-protocol-like. It presents both the optimal and sub-optimal solutions in the form of algorithms, which are designed to be implemented easily by computer routines. It also provides MATLAB (R) routines for the key algorithms. It shows how these methods and algorithms can solve estimation and control problems effectively, and identifies potential research directions and ideas to help readers grasp the field more easily. The novel auxiliary estimator method, which is able to deal with estimators that consist of exponentially increasing terms, is developed to analyze the stability and convergence of the optimal estimator. The book also explores the structure and solvability of the optimal control, i.e. linear quadratic Gaussian control. It develops various sub-optimal but efficient solutions for estimation and control for industrial and practical applications, and analyzes their stability and performance. This is a valuable resource for researchers studying networked control systems, especially those related to non-TCP-like networks. The practicality of the ideas included makes it useful for engineers working with networked control.

The Second Edition of this book includes an abundance of examples to illustrate advanced concepts and brings out in a text book setting the algorithms for bivariate polynomial matrix factorization results that form the basis of two-dimensional systems theory. Algorithms and their implementation using symbolic algebra are emphasized.

Following the emergence of quantum computing, the subsequent quantum revolution will be that of interconnecting individual quantum computers at the global level. In the same way that classical computers only realised their full potential with the emergence of the internet, a fully-realised quantum internet is the next stage of evolution for quantum computation. This cutting-edge book examines in detail how the quantum internet would evolve in practise, focusing not only on the technology itself, but also the implications it will have economically and politically, with numerous non-technical sections throughout the text providing broader context to the discussion. The book begins with a description of classical networks before introducing the key concepts behind quantum networks, such as quantum internet protocols, quantum cryptography, and cloud quantum computing. Written in an engaging style and accessible to graduate students in physics, engineering, computer science and mathematics.

This book offers advanced parallel and distributed algorithms and experimental laboratory prototypes of unconventional shortest path solvers. In addition, it presents novel and unique algorithms of solving shortest problems in massively parallel cellular automaton machines. The shortest path problem is a fundamental and classical problem in graph theory and computer science and is frequently applied in the contexts of transport and logistics, telecommunication networks, virtual reality and gaming, geometry, and social networks analysis. Software implementations include distance-vector algorithms for distributed path computation in dynamics networks, parallel solutions of the constrained shortest path problem, and application of the shortest path solutions in gathering robotic swarms. Massively parallel algorithms utilise cellular automata, where a shortest path is computed either via matrix multiplication in automaton arrays, or via the representation of data graphs in automaton lattices and using the propagation of wave-like patterns. Unconventional shortest path solvers are presented in computer models of foraging behaviour and protoplasmic network optimisation by the slime mould Physarum polycephalum and fluidic devices, while experimental laboratory prototypes of path solvers using chemical media, flows and droplets, and electrical current are also highlighted. The book will be a pleasure to explore for readers from all walks of life, from undergraduate students to university professors, from mathematicians, computers scientists and engineers to chemists and biologists.

This volume includes edited and revised versions of the papers delivered and discussed at the recent Advertising and Consumer Psychology Conference. Following the theme of the conference -- "Measuring Advertising Effectiveness" -- the book blends academic psychology, marketing theory, survey methodology, and practical experience, while simultaneously addressing the problems and limitations of advertising.
Acknowledging that advertisements are subtle, diverse, complex phenomena that require detailed investigation, this compilation explores the multidimensional nature of advertising's diverse effects from both academic and applied perspectives. Updates on theories and methods -- along with expert commentaries -- help to make this a valuable collection that will be of interest to advertising and marketing specialists and communications experts alike.

This open access proceedings volume brings selected, peer-reviewed contributions presented at the Stochastic Transport in Upper Ocean Dynamics (STUOD) 2021 Workshop, held virtually and in person at the Imperial College London, UK, September 20-23, 2021. The STUOD project is supported by an ERC Synergy Grant, and led by Imperial College London, the National Institute for Research in Computer Science and Automatic Control (INRIA) and the French Research Institute for Exploitation of the Sea (IFREMER). The project aims to deliver new capabilities for assessing variability and uncertainty in upper ocean dynamics. It will provide decision makers a means of quantifying the effects of local patterns of sea level rise, heat uptake, carbon storage and change of oxygen content and pH in the ocean. Its multimodal monitoring will enhance the scientific understanding of marine debris transport, tracking of oil spills and accumulation of plastic in the sea. All topics of these proceedings are essential to the scientific foundations of oceanography which has a vital role in climate science. Studies convened in this volume focus on a range of fundamental areas, including: Observations at a high resolution of upper ocean properties such as temperature, salinity, topography, wind, waves and velocity; Large scale numerical simulations; Data-based stochastic equations for upper ocean dynamics that quantify simulation error; Stochastic data assimilation to reduce uncertainty. These fundamental subjects in modern science and technology are urgently required in order to meet the challenges of climate change faced today by human society. This proceedings volume represents a lasting legacy of crucial scientific expertise to help meet this ongoing challenge, for the benefit of academics and professionals in pure and applied mathematics, computational science, data analysis, data assimilation and oceanography.

This text contributes to the field of sequential optimization for finite-state machines, introducing several new provably-optimal algorithms, presenting practical software implementations of each of these algorithms and introducing a complete new CAD package, called MINIMALIST. Real-world industrial designs are used as benchmark circuits throughout.

The widespread interest this book has found among professors, scientists and stu dents working in a variety of fields has made a new edition necessary. I have used this opportunity to add three new chapters on recent developments. One of the most fascinating fields of modern science is cognitive science which has become a meet ing place of many disciplines ranging from mathematics over physics and computer science to psychology. Here, one of the important links between these fields is the concept of information which, however, appears in various disguises, be it as Shan non information or as semantic information (or as something still different). So far, meaning seemed to be exorcised from Shannon information, whereas meaning plays a central role in semantic (or as it is sometimes called "pragmatic") information. In the new chapter 13 it will be shown, however, that there is an important interplay between Shannon and semantic information and that, in particular, the latter plays a decisive role in the fixation of Shannon information and, in cognitive processes, al lows a drastic reduction of that information. A second, equally fascinating and rapidly developing field for mathematicians, computer scientists and physicists is quantum information and quantum computa tion. The inclusion of these topics is a must for any modern treatise dealing with in formation. It becomes more and more evident that the abstract concept of informa tion is inseparably tied up with its realizations in the physical world."

Coding theory came into existence in the late 1940's and is concerned with devising efficient encoding and decoding procedures.
The book is intended as a principal text for first courses in coding and algebraic coding theory, and is aimed at advanced undergraduates and recent graduates as both a course and self-study text. BCH and cyclic, Group codes, Hamming codes, polynomial as well as many other codes are introduced in this textbook. Incorporating numerous worked examples and complete logical proofs, it is an ideal introduction to the fundamental of algebraic coding.

This book presents how federated learning helps to understand and learn from user activity in Internet of Things (IoT) applications while protecting user privacy. The authors first show how federated learning provides a unique way to build personalized models using data without intruding on users' privacy. The authors then provide a comprehensive survey of state-of-the-art research on federated learning, giving the reader a general overview of the field. The book also investigates how a personalized federated learning framework is needed in cloud-edge architecture as well as in wireless-edge architecture for intelligent IoT applications. To cope with the heterogeneity issues in IoT environments, the book investigates emerging personalized federated learning methods that are able to mitigate the negative effects caused by heterogeneities in different aspects. The book provides case studies of IoT based human activity recognition to demonstrate the effectiveness of personalized federated learning for intelligent IoT applications, as well as multiple controller design and system analysis tools including model predictive control, linear matrix inequalities, optimal control, etc. This unique and complete co-design framework will benefit researchers, graduate students and engineers in the fields of control theory and engineering.

This book highlights the capabilities and limitations of radar and air navigation. It discusses issues related to the physical principles of an electromagnetic field, the structure of radar information, and ways to transmit it. Attention is paid to the classification of radio waves used for transmitting radar information, as well as to the physical description of their propagation media. The third part of the book addresses issues related to the current state of navigation systems used in civil aviation and the prospects for their development in the future, as well as the history of satellite radio navigation systems. The book may be useful for schoolchildren, interested in the problems of radar and air navigation.

Appropriate for beginning graduate level courses on linear systems, graduate courses introducing linear control, and for self-study.

The basic theory of linear systems is developed in a unified, accessible, and careful manner, with parallel, independent treatment of continuous-time and discrete-time linear systems. Modest mathematical background is assumed, and the technical presentation is explicit and step-by-step. There are many examples to help the reader, and carefully chosen exercises. Includes extensive, annotated citations. The presentation has been repeatedly class tested and refined.

This book focuses on approximations under the presence of ordinary and fractional smoothness, presenting both the univariate and multivariate cases. It also explores approximations under convexity and a new trend in approximation theory -approximation by sublinear operators with applications to max-product operators, which are nonlinear and rational providing very fast and flexible approximations. The results presented have applications in numerous areas of pure and applied mathematics, especially in approximation theory and numerical analysis in both ordinary and fractional senses. As such this book is suitable for researchers, graduate students, and seminars of the above disciplines, and is a must for all science and engineering libraries.

The recent evolution of western societies has been characterized by an increasing emphasis on information and communication. As the amount of available information increases, however, the user -- worker, student, citizen -- faces a new problem: selecting and accessing relevant information. More than ever it is crucial to find efficient ways for users to interact with information systems in a way that prevents them from being overwhelmed or simply missing their targets. As a result, hypertext systems have been developed as a means of facilitating the interactions between readers and text. In hypertext, information is organized as a network in which nodes are text chunks (e.g., lists of items, paragraphs, pages) and links are relationships between the nodes (e.g., semantic associations, expansions, definitions, examples -- virtually any kind of relation that can be imagined between two text passages). Unfortunately, the many ways in which these hypertext interfaces can be designed has caused a complexity that extends far beyond the processing abilities of regular users. Therefore, it has become widely recognized that a more rational approach based on a thorough analysis of information users' needs, capacities, capabilities, and skills is needed. This volume seeks to meet that need.
From a user-centered perspective -- between systems and users -- this volume presents theoretical and empirical research on the cognitive processes involved in using hypertext. In so doing, it illustrates three main approaches to the design of hypertext systems:
*cognitive, which examines how users process multilayered hypertext structures;
*ergonomical, which explores how users interact with the design characteristics of hardware and software; and
*educational, which studies the learning objectives, frequency and duration of hypertext sessions, type of reading activity, and the user's learning characteristics.
This volume also tries to provide answers for the questions that have plagued hypertext research:
*What is hypertext good for?
*Who is hypertext good for?
*If it is useful for learning and instruction, then what type?
*What particular cognitive skills are needed to interact successfully with a hypertext system? Anyone interested in the fields of computer science, linguistics, psychology, education, and graphic design will find this volume intriguing, informative, and a definitive starting point for future research in the field of hypertext.

Autonomous manipulation is a challenge in robotic technologies. It refers to the capability of a mobile robot system with one or more manipulators that performs intervention tasks requiring physical contacts in unstructured environments and without continuous human supervision. Achieving autonomous manipulation capability is a quantum leap in robotic technologies as it is currently beyond the state of the art in robotics.

This book addresses issues with the complexity of the problems encountered in autonomous manipulation including representation and modeling of robotic structures, kinematic and dynamic robotic control, kinematic and algorithmic singularity avoidance, dynamic task priority, workspace optimization and environment perception. Further development in autonomous manipulation should be able to provide robust improvements of the solutions for all of the above issues. The book provides an extensive tract on sensory-based autonomous manipulation for intervention tasks in unstructured environments. After presenting the theoretical foundations for kinematic and dynamic modelling as well as task-priority based kinematic control of multi-body systems, the work is focused on one of the most advanced underwater vehicle-manipulator system, SAUVIM (Semi-Autonomous Underwater Vehicle for Intervention Missions). Solutions to the problem of target identification and localization are proposed, a number of significant case studies are discussed and practical examples and experimental/simulation results are presented. The book may inspire the robot research community to further investigate critical issues in autonomous manipulation and to develop robot systems that can profoundly impact our society for the better."

This monograph presents new model-based design methods for trajectory planning, feedback stabilization, state estimation, and tracking control of distributed-parameter systems governed by partial differential equations (PDEs). Flatness and backstepping techniques and their generalization to PDEs with higher-dimensional spatial domain lie at the core of this treatise. This includes the development of systematic late lumping design procedures and the deduction of semi-numerical approaches using suitable approximation methods. Theoretical developments are combined with both simulation examples and experimental results to bridge the gap between mathematical theory and control engineering practice in the rapidly evolving PDE control area. The text is divided into five parts featuring: - a literature survey of paradigms and control design methods for PDE systems - the first principle mathematical modeling of applications arising in heat and mass transfer, interconnected multi-agent systems, and piezo-actuated smart elastic structures - the generalization of flatness-based trajectory planning and feedforward control to parabolic and biharmonic PDE systems defined on general higher-dimensional domains - an extension of the backstepping approach to the feedback control and observer design for parabolic PDEs with parallelepiped domain and spatially and time varying parameters - the development of design techniques to realize exponentially stabilizing tracking control - the evaluation in simulations and experiments Control of Higher-Dimensional PDEs - Flatness and Backstepping Designs is an advanced research monograph for graduate students in applied mathematics, control theory, and related fields. The book may serve as a reference to recent developments for researchers and control engineers interested in the analysis and control of systems governed by PDEs.

This book describes the practical application of artificial intelligence (AI) methods using time series data in system control. This book consistently discusses the application of machine learning to the analysis and modelling of time series data of physical quantities to be controlled in the field of system control. Since dynamic systems are not stable steady states but changing transient states, the changing transient states depend on the state history before the change. In other words, it is essential to predict the change from the present to the future based on the time history of each variable in the target system, and to manipulate the system to achieve the desired change. In short, time series is the key to the application of AI machine learning to system control. This is the philosophy of this book: "time series data" + "AI machine learning" = "new practical control methods". This book can give my helps to undergradate or graduate students, institute researchers and senior engineers whose scientific background are engineering, mathematics, physics and other natural sciences.

Autonomy Oriented Computing is a comprehensive reference for scientists, engineers, and other professionals concerned with this promising development in computer science. It can also be used as a text in graduate/undergraduate programs in a broad range of computer-related disciplines, including Robotics and Automation, Amorphous Computing, Image Processing, Programming Paradigms, Computational Biology, etc.

Part One describes the basic concepts and characteristics of an AOC system and enumerates the critical design and engineering issues faced in AOC system development. Part Two gives detailed analyses of methodologies and case studies to evaluate AOC used in problem solving and complex system modeling. The final chapter outlines possibilities for future research and development.

Numerous illustrative examples, experimental case studies, and exercises at the end of each chapter of Autonomy Oriented Computing help particularize and consolidate the methodologies and theories presented.

The book focuses on analysis and design for positive stochastic jump systems. By using multiple linear co-positive Lyapunov function method and linear programming technique, a basic theoretical framework is formed toward the issues of analysis and design for positive stochastic jump systems. This is achieved by providing an in-depth study on several major topics such as stability, time delay, finite-time control, observer design, filter design, and fault detection for positive stochastic jump systems. The comprehensive and systematic treatment of positive systems is one of the major features of the book, which is particularly suited for readers who are interested to learn non-negative theory. By reading this book, the reader can obtain the most advanced analysis and design techniques for positive stochastic jump systems.

This is the first book devoted to radiowave propagation over land and sea. Researchers and engineers involved in propagation studies and applications in communications, broadcasting, radar and remote sensing will find this volume invaluable.

Characterized by its multi-level interdisciplinary character, communication has become a variable field -- one in which the level of analysis varies. This has had important ramifications for the study of communication because, to some extent, the questions one asks are determined by the methods one has available to answer them. As a result, communication research is characterized by the plethora of both qualitative and quantitative approaches used by its practitioners. These include survey and experimental methods, and content, historical, and rhetorical analyses.
A variety of tools has been developed in cognitive psychology and psychophysiology which attempts to measure "thinking" without asking people how they do it. This book is devoted to exploring how these methods might be used to further knowledge about the process of communication. The methods chosen have all been used extensively in cognitive and experimental psychology. Each chapter in this book is designed to describe the history of the method being introduced, the theory behind it, how to go about using it, and how it has already been used to study some area of communication. The methods introduced here vary widely in terms of the amount of equipment and training needed to use them. Some require only theoretical knowledge and a paper and pencil; others require more elaborate hardware and software for implementation. These methods also vary widely in terms of what sorts of variables they can be used to measure. Some of them adapt quite readily to traditional communication variables like persuasion, attitude change, and knowledge; others are more applicable to process type variables such as attention, arousal, involvement, encoding, and retrieval.

This book has a rather strange history. It began in spring 1989, thirteen years after our Systems Science Department at SUNY-Binghamton was established, when I was asked by a group of students in our doctoral program to have a meeting with them. The spokesman of the group, Cliff Joslyn, opened our meeting by stating its purpose. I can closely paraphrase what he said: "We called this meeting to discuss with you, as Chairman of the Department, a fundamental problem with our systems science curriculum. In general, we consider it a good curriculum: we learn a lot of concepts, principles, and methodological tools, mathematical, computational, heu ristic, which are fundamental to understanding and dealing with systems. And, yet, we learn virtually nothing about systems science itself. What is systems science? What are its historical roots? What are its aims? Where does it stand and where is it likely to go? These are pressing questions to us. After all, aren't we supposed to carry the systems science flag after we graduate from this program? We feel that a broad introductory course to systems science is urgently needed in the curriculum. Do you agree with this assessment?" The answer was obvious and, yet, not easy to give: "I agree, of course, but I do not see how the situation could be alleviated in the foreseeable future."