This text provides one of the first book-length studies on the innovative and sustainable development of complex systems in the era of digital transformations, combining quantitative data from several countries with detailed qualitative accounts at the national level. In particular, the book covers the basic concepts, methods, and cutting-edge research on innovation and sustainability in complex systems. Given its scope, the book will be of great interest and value to researchers and practitioners working across the social sciences and in a diverse range of areas in complexity science. Pursuing a multidisciplinary approach, the book is also an ideal resource for advanced undergraduate and graduate level courses in complexity science, sustainability research, economics, and development studies.

This book offers a systematic and rigorous treatment of continuous-time Markov decision processes, covering both theory and possible applications to queueing systems, epidemiology, finance, and other fields. Unlike most books on the subject, much attention is paid to problems with functional constraints and the realizability of strategies. Three major methods of investigations are presented, based on dynamic programming, linear programming, and reduction to discrete-time problems. Although the main focus is on models with total (discounted or undiscounted) cost criteria, models with average cost criteria and with impulsive controls are also discussed in depth. The book is self-contained. A separate chapter is devoted to Markov pure jump processes and the appendices collect the requisite background on real analysis and applied probability. All the statements in the main text are proved in detail. Researchers and graduate students in applied probability, operational research, statistics and engineering will find this monograph interesting, useful and valuable.

The presence of uncertainty in a system description has always been a critical issue in control. The main objective of "Randomized Algorithms for Analysis and Control of Uncertain Systems, with Applications "(Second Edition) is to introduce the reader to the fundamentals of probabilistic methods in the analysis and design of systems subject to deterministic and stochastic uncertainty. The approach propounded by this text guarantees a reduction in the computational complexity of classical control algorithms and in the conservativeness of standard robust control techniques. The second edition has been thoroughly updated to reflect recent research and new applications with chapters on statistical learning theory, sequential methods for control and the scenario approach being completely rewritten.

Features:

. self-contained treatment explaining Monte Carlo and Las Vegas randomized algorithms from their genesis in the principles of probability theory to their use for system analysis;

. development of a novel paradigm for (convex and nonconvex) controller synthesis in the presence of uncertainty and in the context of randomized algorithms;

. comprehensive treatment of multivariate sample generation techniques, including consideration of the difficulties involved in obtaining identically and independently distributed samples;

. applications of randomized algorithms in various endeavours, such as PageRank computation for the Google Web search engine, unmanned aerial vehicle design (both new in the second edition), congestion control of high-speed communications networks and stability of quantized sampled-data systems.

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"Randomized Algorithms for Analysis and Control of Uncertain Systems" (second edition) is certain to interest academic researchers and graduate control students working in probabilistic, robust or optimal control methods and control engineers dealing with system uncertainties.

The present book is a very timely contribution to the literature. I have no hesitation in asserting that it will remain a widely cited reference work for many years.

M. Vidyasagar

"

This book is a useful tool for researchers in both academia and industry who are interested in improving the performances of magnetic recording systems using new coding schemes. Coding and Iterative Detection for Magnetic Recording Channels proposes several new approaches for enhancing the performance of magnetic recording systems by coding and interpolated timing recovery. It provides a tutorial introduction to turbo codes, LDPC codes and their iterative detection schemes. The main emphasis, however, is placed on the simplification of the detector structures for the implementation of various codes. Chapter 1 introduces the model for magnetic recording channels and the challenges to the read channel detector designs. Chapter 2 discusses the turbo codes and the turbo equalization structure for ISI channels. Chapter 3 summarizes the major concepts of LDPC codes and their iterative detection algorithms based on belief propagation. Chapter 4 introduces the Decision Aid Equalization (DAE) structure to simplify iterative detection for ISI channels. Chapter 6 proposes an interpolated timing recovery scheme that facilitates symbol timing recovery by its re-sampling' capability. The combination of the above-mentioned chapters leads to a new structure for implementing iterative detection on recording channels. Chapter 5 deviates from iterative detection to propose a simple code, the Interleaved Parity Check (IPC) code, and its reduced-complexity decoder, which is considered practical for implementation with currently available integrated circuit technology. Chapter 7 summarizes the book with a discussion on future research topics in this field. Coding and Iterative Detection for MagneticRecording Channels is a valuable reference for researchers and design engineers working on signal processing and coding for magnetic recording channels. It may also be used as a graduate text for courses on turbo codes.

Cybernetic pioneer Warren McCullough asked: "What is a man, that he may know a number; and what is a number, that a man may know it?" Thinking along much the same lines, my question here is: "What is a creative mind, that it might emerge from a complex system; and what is a complex system, that it might give rise to a creative mind?" Complexity science is a fashionable topic these days. My perspective on complexity, however, is a somewhat unusual one: I am interested in complex systems science principally as it reflects on abstract mathematical, computational models of mind. In my three previous books, The Structure of Intelligence, Evolving Mind, and Chaotic Logic, I have outlined a comprehensive complex-systems-theoretic theory of mind that I now call the psynet model. This book is a continuation of the research program presented in my previous books (and those books will be frequently referred to here, by the nicknames EM and CL). One might summarize the trajectory of thought spanning these four books as follows. SI formulated a philosophy and mathem- ics of mind, based on theoretical computer science and the concept of "pattern. " EM analyzed the theory of evolution by natural selection in similar terms, and used this computational theory of evolution to establish the evolutionary nature of thought.

This book is a novel tutorial for research-oriented study of vibration mechanics. The book begins with twelve open problems from six case studies of vibration mechanics in order to guide readers in studying the entire book. Then, the book surveys both theories and methods of linear vibrations in an elementary course from a new perspective of aesthetics of science so as to assist readers to upgrade their way of learning. The successive chapters offer a theoretical frame of linear vibrations and waves, covering the models of vibration systems, the vibration analysis of discrete systems, the natural vibrations of one-dimensional structures, the natural vibrations of symmetric structures, and the waves and vibrations of one-dimensional structures. The chapters help readers solve the twelve open problems step by step during the research-oriented study. The book tries to arouse the interest of graduate students and professionals, who have learnt an elementary course of vibration mechanics of two credits, to conduct the research-oriented study and achieve a helical upgrade understanding to vibration mechanics.

In this book, H. S. Green, a former student of Max Born and well known as an author in physics and in philosophy of science, presents an individual and modern approach to theoretical physics and related fundamental problems. Starting from first principles, the links between physics and information science are unveiled step by step: modern information theory and the classical theory of the Turing machine are combined to create a new interpretation of quantum computability, which is then applied to field theory, gravitation and submicroscopic measurement theory and culminates in a detailed examination of the role of the conscious observer in physical measurements. The result is a highly readable book that unifies a wide range of scientific knowledge and is essential reading for all scientists and philosophers of science interested in the interpretation and the implications of the interaction between information science and basic physical theories.

This EMS volume, the first edition of which was published as Dynamical Systems II, EMS 2, sets out to familiarize the reader to the fundamental ideas and results of modern ergodic theory and its applications to dynamical systems and statistical mechanics. The exposition starts from the basic of the subject, introducing ergodicity, mixing and entropy. The ergodic theory of smooth dynamical systems is treated. Numerous examples are presented carefully along with the ideas underlying the most important results. Moreover, the book deals with the dynamical systems of statistical mechanics, and with various kinetic equations. For this second enlarged and revised edition, published as Mathematical Physics I, EMS 100, two new contributions on ergodic theory of flows on homogeneous manifolds and on methods of algebraic geometry in the theory of interval exchange transformations were added. This book is compulsory reading for all mathematicians working in this field, or wanting to learn about it.

This book collects the latest results and new trends in the application of mathematics to some problems in control theory, numerical simulation and differential equations. The work comprises the main results presented at a thematic minisymposium, part of the 9th International Congress on Industrial and Applied Mathematics (ICIAM 2019), held in Valencia, Spain, from 15 to 18 July 2019. The topics covered in the 6 peer-review contributions involve applications of numerical methods to real problems in oceanography and naval engineering, as well as relevant results on switching control techniques, which can have multiple applications in industrial complexes, electromechanical machines, biological systems, etc. Problems in control theory, as in most engineering problems, are modeled by differential equations, for which standard solving procedures may be insufficient. The book also includes recent geometric and analytical methods for the search of exact solutions for differential equations, which serve as essential tools for analyzing problems in many scientific disciplines.

This book reflects the outcome of contribution by the plural community and of the interactions between disciplines. With the mass of data available through Information and Communication Technologies (ICT) in an unprecedented quantity since the Human History, it is now possible to access dimensions of knowledge that, though not hidden, could not be grasped in the same way in the past. The question of how this information can be used for the benefit of institutional and economic actors to foster the development of a territory. Tackling the issue from a resolutely interdisciplinary perspective, the authors explore the theories and methods of complex systems in order to discuss how they can contribute in these new circumstances to territorial intelligence and to the development practices in which it is embodied. This book illustrates how today's research explores the multiple facets of territorial systems in order to reproduce their richness. It invites readers to learn about the challenges, ideas, results and advances present in this domain.

This innovative monograph explores a new mathematical formalism in higher-order temporal logic for proving properties about the behavior of systems. Developed by the authors, the goal of this novel approach is to explain what occurs when multiple, distinct system components interact by using a category-theoretic description of behavior types based on sheaves. The authors demonstrate how to analyze the behaviors of elements in continuous and discrete dynamical systems so that each can be translated and compared to one another. Their temporal logic is also flexible enough that it can serve as a framework for other logics that work with similar models. The book begins with a discussion of behavior types, interval domains, and translation invariance, which serves as the groundwork for temporal type theory. From there, the authors lay out the logical preliminaries they need for their temporal modalities and explain the soundness of those logical semantics. These results are then applied to hybrid dynamical systems, differential equations, and labeled transition systems. A case study involving aircraft separation within the National Airspace System is provided to illustrate temporal type theory in action. Researchers in computer science, logic, and mathematics interested in topos-theoretic and category-theory-friendly approaches to system behavior will find this monograph to be an important resource. It can also serve as a supplemental text for a specialized graduate topics course.

This textbook helps graduate level student to understand easily the linearization of nonlinear control system. Differential geometry is essential to understand the linearization problems of the control nonlinear systems. In this book, the basics of differential geometry needed in linearization are explained on the Euclidean space instead of the manifold for students who are not accustomed to differential geometry. Many Lie algebra formulas, used often in linearization, are also provided with proof. The conditions in the linearization problems are complicated to check because the Lie bracket calculation of vector fields by hand needs much concentration and time. This book provides MATLAB programs for most of the theorems. The book also includes end-of-chapter problems and other pedagogical aids to help understanding and self study.

As internet technologies continue to advance, new types and methods of data and security breaches threaten national security. These potential breaches allow for information theft and can provide footholds for terrorist and criminal organizations. Developments in Information Security and Cybernetic Wars is an essential research publication that covers cyberwarfare and terrorism globally through a wide range of security-related areas. Featuring topics such as crisis management, information security, and governance, this book is geared toward practitioners, academicians, government officials, military professionals, and industry professionals.

This fascinating book examines some of the characteristics of technological/engineering models that are likely to be unfamiliar to those who are interested primarily in the history and philosophy of science and mathematics, and which differentiate technological models from scientific and mathematical ones. Themes that are highlighted include:
the role of language: the models developed for engineering design have resulted in new ways of talking about technological systems
communities of practice: related to the previous point, particular engineering communities have particular ways of sharing and developing knowledge
graphical (re)presentation: engineers have developed many ways of reducing quite complex mathematical models to more simple representations
reification: highly abstract mathematical models are turned into 'objects' that can be manipulated almost like components of a physical system
machines: not only the currently ubiquitous digital computer, but also older analogue devices - slide rules, physical models, wind tunnels and other small-scale simulators, as well as mechanical, electrical and electronic analogue computers
mathematics and modelling as a bridging tool between disciplines
This book studies primarily modelling in technological practice. It is worth noting that models of the type considered in the book are not always highly valued in formal engineering education at university level, which often takes an "applied science" approach close to that of the natural sciences (something that can result in disaffection on the part of students). Yet in an informal context, such as laboratories, industrial placements, and so on, a very different situation obtains. A number of chapters considers such epistemological aspects, as well as the status of different types of models within the engineering education community.
The book will be of interest to practising engineers and technologists; sociologists of science and technology; and historians and philosophers of science and mathematics. It will also be written in a way that will be accessible to non-specialists."

This book develops analytical methods for studying the dynamical chaos, synchronization, and dynamics of structures in various models of coupled rotators. Rotators and their systems are defined in a cylindrical phase space, and, unlike oscillators, which are defined in Rn, they have a wider "range" of motion: There are vibrational and rotational types for cyclic variables, as well as their combinations (rotational-vibrational) if the number of cyclic variables is more than one. The specificity of rotator phase space poses serious challenges in terms of selecting methods for studying the dynamics of related systems. The book chiefly focuses on developing a modified form of the method of averaging, which can be used to study the dynamics of rotators. In general, the book uses the "language" of the qualitative theory of differential equations, point mappings, and the theory of bifurcations, which helps authors to obtain new results on dynamical chaos in systems with few degrees of freedom. In addition, a special section is devoted to the study and classification of dynamic structures that can occur in systems with a large number of interconnected objects, i.e. in lattices of rotators and/or oscillators. Given its scope and format, the book can be used both in lectures and courses on nonlinear dynamics, and in specialized courses on the development and operation of relevant systems that can be represented by a large number of various practical systems: interconnected grids of various mechanical systems, various types of networks including not only mechanical but also biological systems, etc.

In this short monograph Newton-like and other similar numerical methods with applications to solving multivariate equations are developed, which involve Caputo type fractional mixed partial derivatives and multivariate fractional Riemann-Liouville integral operators. These are studied for the first time in the literature. The chapters are self-contained and can be read independently. An extensive list of references is given per chapter. The book's results are expected to find applications in many areas of applied mathematics, stochastics, computer science and engineering. As such this short monograph is suitable for researchers, graduate students, to be used in graduate classes and seminars of the above subjects, also to be in all science and engineering libraries.

How to draw plausible conclusions from uncertain and conflicting sources of evidence is one of the major intellectual challenges of Artificial Intelligence. It is a prerequisite of the smart technology needed to help humans cope with the information explosion of the modern world. In addition, computational modelling of uncertain reasoning is a key to understanding human rationality. Previous computational accounts of uncertain reasoning have fallen into two camps: purely symbolic and numeric. This book represents a major advance by presenting a unifying framework which unites these opposing camps. The Incidence Calculus can be viewed as both a symbolic and a numeric mechanism. Numeric values are assigned indirectly to evidence via the possible worlds in which that evidence is true. This facilitates purely symbolic reasoning using the possible worlds and numeric reasoning via the probabilities of those possible worlds. Moreover, the indirect assignment solves some difficult technical problems, like the combinat ion of dependent sources of evidcence, which had defeated earlier mechanisms. Weiru Liu generalises the Incidence Calculus and then compares it to a succes sion of earlier computational mechanisms for uncertain reasoning: Dempster-Shafer Theory, Assumption-Based Truth Maintenance, Probabilis tic Logic, Rough Sets, etc. She shows how each of them is represented and interpreted in Incidence Calculus. The consequence is a unified mechanism which includes both symbolic and numeric mechanisms as special cases. It provides a bridge between symbolic and numeric approaches, retaining the advantages of both and overcoming some of their disadvantages."

This book focuses on fault diagnosis for linear discrete time-varying (LDTV) systems and its applications in modern engineering processes, with more weighting placed on the development of theory and methodologies. A comprehensive and systematic study on fault diagnosis for LDTV systems is provided, covering H -optimization-based fault diagnosis, H -filtering-based fault diagnosis, parity space-based fault diagnosis, Krein space technique-aided fault detection and fault estimation, and their typical applications in linear/nonlinear processes such as satellite attitude control systems and INS/GPS systems. This book benefits researchers, engineers, and graduate students in the fields of control engineering, electrical and electronic engineering, instrumentation science, and optoelectronic engineering.

This book describes the research progress of the control design about strict-feedback nonlinear systems. A novel gain control design method is proposed, which greatly simplifies the construction procedure of controller for strict-feedback nonlinear systems. The control design problem of strict-feedback nonlinear systems is converted into the determination problem of gain parameters or the construction of dynamic gain equations. Therefore, the tedious iterative design procedure is effectively avoided. This book can be used as a reference for researchers in the field of control theory and engineers seeking advanced methods in practical control applications. 

This book aims to extend existing works on consensus of multi-agent systems systematically. The agents to be considered range from double integrators to generic linear systems. The primary goal is to explicitly characterize how agent parameters, which reflect both self-dynamics and inner coupling of each agent, and switching network topologies jointly influence the collective behaviors. A series of necessary and/or sufficient conditions for exponential consensus are derived. The contents of this book are as follows. Chapter 1 provides the background and briefly reviews the advances of consensus of multi-agent systems. Chapter 2 addresses the consensus problem of double integrators over directed switching network topologies. It is proven that exponential consensus can be secured under very mild conditions incorporating the damping gain and network topology. Chapter 3 considers generic linear systems with undirected switching network topologies. Necessary and sufficient conditions on agent parameters and connectivity of the communication graph for exponential consensus are provided. Chapter 4 furthers the study of consensus for multiple generic linear systems by considering directed switching network topologies. How agent parameters and joint connectivity work together for reaching consensus is characterized from an algebraic and geometric view. Chapter 5 extends the design and analysis methodology to containment control problem, where there exist multiple leaders. A novel analysis framework from the perspective of state transition matrix is developed. This framework relates containment to consensus and overcomes the difficulty of construction of a containment error. This book serves as a reference to the main research issues and results on consensus of multi-agent systems. Some prerequisites for reading this book include linear system theory, matrix theory, mathematics, and so on.

Why is it that many large public projects run out of control in terms of scope, budget and time? How can it be explained that urban regeneration programs are highly successful in one neighborhood but fail to deliver in an adjacent neighborhood? Why is it that public policies can return unexpected and sometimes even unwanted outcomes, despite meticulous planning? Why is public decision-making such a complex affair? The world is an erratic place, full of surprises, some of which are wanted and others are unwanted. Public decision-making in this world is like punching clouds: considerable energy is put into the punching but the cloud goes its own way, despite the punches. Recent ideas and insights from the complexity sciences improve our understanding of the intricate nature of public decision-making. This book offers a bridge between the study of public decision-making in the domain of Public Administration on the one hand, and the complexity sciences on the other hand. It is aimed at (doctoral) students and scholars in Public Administration who are curious about how the complexity sciences can inform the analysis and understanding of public decision-making. The book introduces important concepts such as systems, non-linear dynamics, self-organization and coevolution, and discusses their relevance to public decision-making. It also proposes a case-based research method for researching this complexity. Lasse Gerrits, Ph.D. is associate professor in Public Administration at the Erasmus University Rotterdam (the Netherlands) and member of the research group Governance of Complex Systems.

Networks surround us, from social networks to protein - protein interaction networks within the cells of our bodies. The theory of random graphs provides a necessary framework for understanding their structure and development. This text provides an accessible introduction to this rapidly expanding subject. It covers all the basic features of random graphs - component structure, matchings and Hamilton cycles, connectivity and chromatic number - before discussing models of real-world networks, including intersection graphs, preferential attachment graphs and small-world models. Based on the authors' own teaching experience, it can be used as a textbook for a one-semester course on random graphs and networks at advanced undergraduate or graduate level. The text includes numerous exercises, with a particular focus on developing students' skills in asymptotic analysis. More challenging problems are accompanied by hints or suggestions for further reading.

This book is dedicated to the analysis and modelling of fractional behaviours that mainly result from physical stochastic phenomena (diffusion, adsorption or aggregation, etc.) of a population (ions, molecules, people, etc.) in a constrained environment and that can be found in numerous areas. It breaks with the usual approaches based on fractional models since it proposes to use unusual models which have the advantage of overcoming some of the limitations of fractional models. This book is dedicated to postgraduated students and to researchers in the field or those who wish to learn with a fresh perspective. After a review of fractional models and their limitations, it proposes and demonstrates the interest of four other modelling tools to capture fractional behaviours: new kernels in integral operators, Volterra equations, nonlinear models and partial differential equations with spatially variable coefficients. Several applications on real data and devices illustrate their efficiency.