The asymptotic behaviour, in particular "stability" in some sense, is studied systematically for discrete and for continuous linear dynamical systems on Banach spaces. Of particular concern is convergence to an equilibrium with respect to various topologies. Parallels and differences between the discrete and the continuous situation are emphasised.

As a collection of ideas and methodologies, systems thinking has made an impact in organizations and in particular in the information systems field. However, this main emphasis on organizations limits the scope of systems thinking and practice. There is a need first to use systems thinking in addressing societal problems, and second to enable people involved in developing the information society to reflect on the impacts of systems and technologies in society as a whole. Thus, there are opportunities to review the scope and potential of systems thinking and practice to deal with information society-related issues.

Systems Practice in the Information Society provides students of information systems as well as practicing Inofrmation Systems managers with concepts and strategies to enable them to understand and use systems thinking methodologies and address challenges posed by the development of information-based societies. This book brings experiences, ideas, and applications of systemic thinking in designing and evaluating socio-technological initiatives. Using a number of cultural contexts, this book explores how organizations, including governments, can enable better access to information and communication technologies and improve the quality of life of individuals.

As a collection of ideas and methodologies, systems thinking has made an impact in organizations and in particular in the information systems field. However, this main emphasis on organizations limits the scope of systems thinking and practice. There is a need first to use systems thinking in addressing societal problems, and second to enable people involved in developing the information society to reflect on the impacts of systems and technologies in society as a whole. Thus, there are opportunities to review the scope and potential of systems thinking and practice to deal with information society-related issues.

Systems Practice in the Information Society provides students of information systems as well as practicing Inofrmation Systems managers with concepts and strategies to enable them to understand and use systems thinking methodologies and address challenges posed by the development of information-based societies. This book brings experiences, ideas, and applications of systemic thinking in designing and evaluating socio-technological initiatives. Using a number of cultural contexts, this book explores how organizations, including governments, can enable better access to information and communication technologies and improve the quality of life of individuals.

This monograph explores the modeling of conservation and balance laws of one-dimensional hyperbolic systems using partial differential equations. It presents typical examples of hyperbolic systems for a wide range of physical engineering applications, allowing readers to understand the concepts in whichever setting is most familiar to them. With these examples, it also illustrates how control boundary conditions may be defined for the most commonly used control devices. The authors begin with the simple case of systems of two linear conservation laws and then consider the stability of systems under more general boundary conditions that may be differential, nonlinear, or switching. They then extend their discussion to the case of nonlinear conservation laws and demonstrate the use of Lyapunov functions in this type of analysis. Systems of balance laws are considered next, starting with the linear variety before they move on to more general cases of nonlinear ones. They go on to show how the problem of boundary stabilization of systems of two balance laws by both full-state and dynamic output feedback in observer-controller form is solved by using a "backstepping" method, in which the gains of the feedback laws are solutions of an associated system of linear hyperbolic PDEs. The final chapter presents a case study on the control of navigable rivers to emphasize the main technological features that may occur in real live applications of boundary feedback control. Stability and Boundary Stabilization of 1-D Hyperbolic Systems will be of interest to graduate students and researchers in applied mathematics and control engineering. The wide range of applications it discusses will help it to have as broad an appeal within these groups as possible.

The aim of this Book is to give an overview, based on the results of nearly three decades of intensive research, of transient chaos. One belief that motivates us to write this book is that, transient chaos may not have been appreciated even within the nonlinear-science community, let alone other scientific disciplines.

Heavy tails -extreme events or values more common than expected -emerge everywhere: the economy, natural events, and social and information networks are just a few examples. Yet after decades of progress, they are still treated as mysterious, surprising, and even controversial, primarily because the necessary mathematical models and statistical methods are not widely known. This book, for the first time, provides a rigorous introduction to heavy-tailed distributions accessible to anyone who knows elementary probability. It tackles and tames the zoo of terminology for models and properties, demystifying topics such as the generalized central limit theorem and regular variation. It tracks the natural emergence of heavy-tailed distributions from a wide variety of general processes, building intuition. And it reveals the controversy surrounding heavy tails to be the result of flawed statistics, then equips readers to identify and estimate with confidence. Over 100 exercises complete this engaging package.

After a short introduction to the fundamentals, this book provides a detailed account of major advances in applying fractional calculus to dynamical systems. Fractional order dynamical systems currently continue to gain further importance in many areas of science and engineering. As with many other approaches to mathematical modeling, the first issue to be addressed is the need to couple a definition of the fractional differentiation or integration operator with the types of dynamical systems that are analyzed. As such, for the fundamentals the focus is on basic aspects of fractional calculus, in particular stability analysis, which is required to tackle synchronization in coupled fractional order systems, to understand the essence of estimators for related integer order systems, and to keep track of the interplay between synchronization and parameter observation. This serves as the common basis for the more advanced topics and applications presented in the subsequent chapters, which include an introduction to the 'Immersion and Invariance' (I&I) methodology, the masterslave synchronization scheme for partially known nonlinear fractional order systems, Fractional Algebraic Observability (FAO) and Fractional Generalized quasi-Synchronization (FGqS) to name but a few. This book is intended not only for applied mathematicians and theoretical physicists, but also for anyone in applied science dealing with complex nonlinear systems.

recently discovered advantages of amorphous forms of medicines/pharmaceutical products which focused a significant part of industry-related efforts on the GFA (Glass Forming Ability) and the glass temperature (T) versus pressure g dependences. 1 b ? 0 ? ? o ? P ? Pg P ? Pg 0 ? ? ? ? T (P ) = F (P )D (P ) =T 1 + exp ? g g ? 0 ? ? ? ? c + Pg ? ? ? ? 400 1 b 0 o ? ? ? ? P ? P P ? P g g 0 ? ? ? ? T (P ) = F (P )D (P ) =T 1 + exp ? g g 0 ? ? ? ? c ? + P max g ? ? ? ? T ~7 GPa g max P ~ 304 K Liquid g 300 1 HS glass 0 200 -1 mSG ?=0. 044 Liquid -2 100 -3 glass ?=0. 12 -1. 2 -0. 9 -0. 6 -0. 3 0. 0 log T 10 scaled -1 0 1 2 3 4 5 6 7 8 9 10 11 12 P (GPa) g 19 Figure 1. T he pressure evolution of the glass temperature in gl Th ye s cerol ol . id curve shows the parameterization of experimental data via the novel, modifie d Glat Sizm elon type equation, given in the Figure.

The subject of the book is to present the modeling, parameter estimation and other aspects of the identification of nonlinear dynamic systems. The treatment is restricted to the input-output modeling approach. Because of the widespread usage of digital computers discrete time methods are preferred. Time domain parameter estimation methods are dealt with in detail, frequency domain and power spectrum procedures are described shortly. The theory is presented from the engineering point of view, and a large number of examples of case studies on the modeling and identifications of real processes illustrate the methods. Almost all processes are nonlinear if they are considered not merely in a small vicinity of the working point. To exploit industrial equipment as much as possible, mathematical models are needed which describe the global nonlinear behavior of the process. If the process is unknown, or if the describing equations are too complex, the structure and the parameters can be determined experimentally, which is the task of identification. The book is divided into seven chapters dealing with the following topics: 1. Nonlinear dynamic process models 2. Test signals for identification 3. Parameter estimation methods 4. Nonlinearity test methods 5. Structure identification 6. Model validity tests 7. Case studies on identification of real processes Chapter I summarizes the different model descriptions of nonlinear dynamical systems.

This book presents the latest researches on hypersonic steady glide dynamics and guidance, including the concept of steady glide reentry trajectory and the stability of its regular perturbation solutions, trajectory damping control technique for hypersonic glide reentry, singular perturbation guidance of hypersonic glide reentry, trajectory optimization based on steady glide, linear pseudospectral generalized nominal effort miss distance guidance, analytical entry guidance and trajectory-shaping guidance with final speed and load factor constraints. They can be used to solve many new difficult problems in entry guidance. And many practical engineering cases are provided for the readers for better understanding. Researchers and students in the fields of flight vehicle design or flight dynamics, guidance and control could use the book as valuable reference.

As lives offline and online merge even more, it is easy to forget how we got here. Rise of the Machines reclaims the spectacular story of cybernetics, one of the twentieth century's pivotal ideas. Springing from the mind of mathematician Norbert Wiener amid the devastation of World War II, the cybernetic vision underpinned a host of seductive myths about the future of machines. Cybernetics triggered blissful cults and military gizmos, the Whole Earth Catalog and the air force's foray into virtual space, as well as crypto-anarchists fighting for internet freedom. In Rise of the Machines, Thomas Rid draws on unpublished sources-including interviews with hippies, anarchists, sleuths, and spies-to offer an unparalleled perspective into our anxious embrace of technology.

This book presents a comprehensive mathematical theory that explains precisely what information flow is, how it can be assessed quantitatively - so bringing precise meaning to the intuition that certain information leaks are small enough to be tolerated - and how systems can be constructed that achieve rigorous, quantitative information-flow guarantees in those terms. It addresses the fundamental challenge that functional and practical requirements frequently conflict with the goal of preserving confidentiality, making perfect security unattainable. Topics include: a systematic presentation of how unwanted information flow, i.e., "leaks", can be quantified in operationally significant ways and then bounded, both with respect to estimated benefit for an attacking adversary and by comparisons between alternative implementations; a detailed study of capacity, refinement, and Dalenius leakage, supporting robust leakage assessments; a unification of information-theoretic channels and information-leaking sequential programs within the same framework; and a collection of case studies, showing how the theory can be applied to interesting realistic scenarios. The text is unified, self-contained and comprehensive, accessible to students and researchers with some knowledge of discrete probability and undergraduate mathematics, and contains exercises to facilitate its use as a course textbook.

Dynamic Programming for Impulse Feedback and Fast Controls offers a description of feedback control in the class of impulsive inputs. This book deals with the problem of closed-loop impulse control based on generalization of dynamic programming techniques in the form of variational inequalities of the Hamilton-Jacobi-Bellman type. It provides exercises and examples in relation to software, such as techniques for regularization of ill-posed problems. It also gives an introduction to applications such as hybrid dynamics, control in arbitrary small time, and discontinuous trajectories.This book walks the readers through: the design and description of feedback solutions for impulse controls; the explanation of impulses of higher order that are derivatives of delta functions; the description of their physically realizable approximations - the fast controls and their approximations; the treatment of uncertainty in impulse control and the applications of impulse feedback. Of interest to both academics and graduate students in the field of control theory and applications, the book also protects users from common errors , such as inappropriate solution attempts, by indicating Hamiltonian techniques for hybrid systems with resets.

In concurrent and distributed systems, processes can complete tasks together by playing their parts in a joint plan. The plan, or protocol, can be written as a choreography: a formal description of overall behaviour that processes should collaborate to implement, like authenticating a user or purchasing an item online. Formality brings clarity, but not only that: choreographies can contribute to important safety and liveness properties. This book is an ideal introduction to theory of choreographies for students, researchers, and professionals in computer science and applied mathematics. It covers languages for writing choreographies, their semantics, and principles for implementing choreographies correctly. The text treats the study of choreographies as a discipline in its own right, following a systematic approach that starts from simple foundations and proceeds to more advanced features in incremental steps. Each chapter includes examples and exercises aimed at helping with understanding the theory and its relation to practice.

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 deals with the autoregressive method for digital processing of random oscillations. The method is based on a one-to-one transformation of the numeric factors of the Yule series model to linear elastic system characteristics. This parametric approach allowed to develop a formal processing procedure from the experimental data to obtain estimates of logarithmic decrement and natural frequency of random oscillations. A straightforward mathematical description of the procedure makes it possible to optimize a discretization of oscillation realizations providing efficient estimates. The derived analytical expressions for confidence intervals of estimates enable a priori evaluation of their accuracy. Experimental validation of the method is also provided. Statistical applications for the analysis of mechanical systems arise from the fact that the loads experienced by machineries and various structures often cannot be described by deterministic vibration theory. Therefore, a sufficient description of real oscillatory processes (vibrations) calls for the use of random functions. In engineering practice, the linear vibration theory (modeling phenomena by common linear differential equations) is generally used. This theory's fundamental concepts such as natural frequency, oscillation decrement, resonance, etc. are credited for its wide use in different technical tasks. In technical applications two types of research tasks exist: direct and inverse. The former allows to determine stochastic characteristics of the system output X(t) resulting from a random process E(t) when the object model is considered known. The direct task enables to evaluate the effect of an operational environment on the designed object and to predict its operation under various loads. The inverse task is aimed at evaluating the object model on known processes E(t) and X(t), i.e. finding model (equations) factors. This task is usually met at the tests of prototypes to identify (or verify) its model experimentally. To characterize random processes a notion of "shaping dynamic system" is commonly used. This concept allows to consider the observing process as the output of a hypothetical system with the input being stationary Gauss-distributed ("white") noise. Therefore, the process may be exhaustively described in terms of parameters of that system. In the case of random oscillations, the "shaping system" is an elastic system described by the common differential equation of the second order: X (t)+2hX (t)+ _0^2 X(t)=E(t), where 0 = 2 / 0 is the natural frequency, T0 is the oscillation period, and h is a damping factor. As a result, the process X(t) can be characterized in terms of the system parameters - natural frequency and logarithmic oscillations decrement = hT0 as well as the process variance. Evaluation of these parameters is subjected to experimental data processing based on frequency or time-domain representations of oscillations. It must be noted that a concept of these parameters evaluation did not change much during the last century. For instance, in case of the spectral density utilization, evaluation of the decrement values is linked with bandwidth measurements at the points of half-power of the observed oscillations. For a time-domain presentation, evaluation of the decrement requires measuring covariance values delayed by a time interval divisible by T0. Both estimation procedures are derived from a continuous description of research phenomena, so the accuracy of estimates is linked directly to the adequacy of discrete representation of random oscillations. This approach is similar a concept of transforming differential equations to difference ones with derivative approximation by corresponding finite differences. The resulting discrete model, being an approximation, features a methodical error which can be decreased but never eliminated. To render such a presentation more accurate it is imperative to decrease the discretization interval and to increase realization size growing requirements for computing power. The spectral density and covariance function estimates comprise a non-parametric (non-formal) approach. In principle, any non-formal approach is a kind of art i.e. the results depend on the performer's skills. Due to interference of subjective factors in spectral or covariance estimates of random signals, accuracy of results cannot be properly determined or justified. To avoid the abovementioned difficulties, the application of linear time-series models with well-developed procedures for parameter estimates is more advantageous. A method for the analysis of random oscillations using a parametric model corresponding discretely (no approximation error) with a linear elastic system is developed and presented in this book. As a result, a one-to-one transformation of the model's numerical factors to logarithmic decrement and natural frequency of random oscillations is established. It allowed to develop a formal processing procedure from experimental data to obtain the estimates of and 0. The proposed approach allows researchers to replace traditional subjective techniques by a formal processing procedure providing efficient estimates with analytically defined statistical uncertainties.

This book reports on the development and assessment of a novel framework for studying neural interactions (the connectome) and their dynamics (the chronnectome). Using EEG recordings taken during an auditory oddball task performed by 48 patients with schizophrenia and 87 healthy controls, and applying local and network measures, changes in brain activation from pre-stimulus to cognitive response were assessed, and significant differences were observed between the patients and controls. This book investigates the source of the network abnormalities and presents new evidence for the disconnection hypothesis and the aberrant salience hypothesis with regard to schizophrenia. Moreover, it puts forward a novel approach to combining local regularity measures and graph measures in order to characterize schizophrenia brain dynamics, and presents interesting findings on the regularity of brain patterns in healthy control subjects versus patients with schizophrenia. Besides providing new evidence for the disconnection hypothesis, it offers a source of inspiration for future research directions in the field.

This book on complexity science comprises a collection of chapters on methods and principles from a wide variety of disciplinary fields - from physics and chemistry to biology and the social sciences.In this two-part volume, the first part is a collection of chapters introducing different aspects in a coherent fashion, and providing a common basis and the founding principles of the different complexity science approaches; the next provides deeper discussions of the different methods of use in complexity science, with interesting illustrative applications.The fundamental topics deal with self-organization, pattern formation, forecasting uncertainties, synchronization and revolutionary change, self-adapting and self-correcting systems, and complex networks. Examples are taken from biology, chemistry, engineering, epidemiology, robotics, economics, sociology, and neurology.

Learn to solve the unprecedented challenges facing Online Learning and Adaptive Signal Processing in this concise, intuitive text. The ever-increasing amount of data generated every day requires new strategies to tackle issues such as: combining data from a large number of sensors; improving spectral usage, utilizing multiple-antennas with adaptive capabilities; or learning from signals placed on graphs, generating unstructured data. Solutions to all of these and more are described in a condensed and unified way, enabling you to expose valuable information from data and signals in a fast and economical way. The up-to-date techniques explained here can be implemented in simple electronic hardware, or as part of multi-purpose systems. Also featuring alternative explanations for online learning, including newly developed methods and data selection, and several easily implemented algorithms, this one-of-a-kind book is an ideal resource for graduate students, researchers, and professionals in online learning and adaptive filtering.

At the dawn of the twenty-first century, education about and through the media has become a worldwide phenomenon, and is playing an increasingly important role in educational reform. The theory and practice of media education have profited greatly from recent and intensive development and application of new information and telecommunications technologies. Consequently, the importance of media and information literacy is taking on an even greater urgency. With this in mind, the contributors to this volume survey what has taken place over the last decade in different parts of the world, examine the current state of theoretical, conceptual, and research development, and consider where media education is going and where it ought to go.

With two-thirds of its 22 contributions coming from outside the United States, "Media Literacy in the Information Age" is a genuine international effort, with many leading media and information educators in the world taking part. The work converts the notion of globalism from a slogan into a working hypothesis. The concerns in this volume are with literacy not just in computer technology, but as a broad concern of the educational process.

Discover the foundations of quantum mechanics, and explore how these principles are powering a new generation of advances in quantum engineering, in this ground-breaking undergraduate textbook. It explains physical and mathematical principles using cutting-edge electronic, optoelectronic and photonic devices, linking underlying theory with real-world applications; focuses on current technologies and avoids historic approaches, getting students quickly up-to-speed to tackle contemporary engineering challenges; provides an introduction to the foundations of quantum information, and a wealth of real-world quantum examples, including quantum well infrared photodetectors, solar cells, quantum teleportation, quantum computing, band gap engineering, quantum cascade lasers, low-dimensional materials, and van der Waals heterostructures; and includes pedagogical features such as objectives and end-of-chapter homework problems to consolidate student understanding, and solutions for instructors. Designed to inspire the development of future quantum devices and systems, this is the perfect introduction to quantum mechanics for undergraduate electrical engineers and materials scientists.

"SSM offers an elegantly simple approach that is both powerful, yet non-threatening and one that forces organisations to confront questions essential to their very survival such as, "Are we doing the right thing?"
From the Foreword by Mike Duffy, Operations Director, The Smith Group

Since its inception more than thirty years ago, the benefits of using Soft Systems Methodology for problem solving has gained worldwide recognition. Yet, despite recognising the importance of SSM, students and practitioners still experience considerable difficulty with the intellectual process involved.

Based on a lifetime experience as an academic and consultant, Brian Wilson provides guidance on how to develop a range of conceptual models across a variety of business problems. Building on his earlier work in Systems: Concepts, Methodologies and Applications he takes a practical approach to the topic based on the premise that all organisations are unique. He develops concepts to articulate ways of thinking about complexity. These are an alternative to mathematically-based concepts, and they offer rigorous, and defensible ways of answering the question 'What do we take the organisation to be?' A model of the most appropriate and relevant concept for your own organisation can then be successfully developed and applied.

Of relevance to organisations of any type, or any size, this book shows how model building within SSM can be used to cope with real-life problems. It will be an invaluable resource for students and practitioners in both the public and private sectors.

This compact course is written for the mathematically literate reader who wants to learn to analyze data in a principled fashion. The language of mathematics enables clear exposition that can go quite deep, quite quickly, and naturally supports an axiomatic and inductive approach to data analysis. Starting with a good grounding in probability, the reader moves to statistical inference via topics of great practical importance - simulation and sampling, as well as experimental design and data collection - that are typically displaced from introductory accounts. The core of the book then covers both standard methods and such advanced topics as multiple testing, meta-analysis, and causal inference.

Compound renewal processes (CRPs) are among the most ubiquitous models arising in applications of probability. At the same time, they are a natural generalization of random walks, the most well-studied classical objects in probability theory. This monograph, written for researchers and graduate students, presents the general asymptotic theory and generalizes many well-known results concerning random walks. The book contains the key limit theorems for CRPs, functional limit theorems, integro-local limit theorems, large and moderately large deviation principles for CRPs in the state space and in the space of trajectories, including large deviation principles in boundary crossing problems for CRPs, with an explicit form of the rate functionals, and an extension of the invariance principle for CRPs to the domain of moderately large and small deviations. Applications establish the key limit laws for Markov additive processes, including limit theorems in the domains of normal and large deviations.