Bayesian Inference of State Space Models: Kalman Filtering and Beyond offers a comprehensive introduction to Bayesian estimation and forecasting for state space models. The celebrated Kalman filter, with its numerous extensions, takes centre stage in the book. Univariate and multivariate models, linear Gaussian, non-linear and non-Gaussian models are discussed with applications to signal processing, environmetrics, economics and systems engineering. Over the past years there has been a growing literature on Bayesian inference of state space models, focusing on multivariate models as well as on non-linear and non-Gaussian models. The availability of time series data in many fields of science and industry on the one hand, and the development of low-cost computational capabilities on the other, have resulted in a wealth of statistical methods aimed at parameter estimation and forecasting. This book brings together many of these methods, presenting an accessible and comprehensive introduction to state space models. A number of data sets from different disciplines are used to illustrate the methods and show how they are applied in practice. The R package BTSA, created for the book, includes many of the algorithms and examples presented. The book is essentially self-contained and includes a chapter summarising the prerequisites in undergraduate linear algebra, probability and statistics. An up-to-date and complete account of state space methods, illustrated by real-life data sets and R code, this textbook will appeal to a wide range of students and scientists, notably in the disciplines of statistics, systems engineering, signal processing, data science, finance and econometrics. With numerous exercises in each chapter, and prerequisite knowledge conveniently recalled, it is suitable for upper undergraduate and graduate courses.

For the past 50 years, the advancements of technology have equipped architects with unique tools that have enabled the development of new computer-mediated design methods, fabrication techniques, and architectural expressions. Simultaneously, in contemporary architecture new frameworks emerged that have radically redefined the traditional conceptions of design, of the built environment, and of the role of architects. Cybernetic Architectures argues that such frameworks have been constructed in direct reference to cybernetic thinking, a thought model that emerged concurrently with the origins of informatics and that embodies the main assumptions, values, and ideals underlying the development of computer science. The book explains how the evolution of the computational perspective in architecture has been parallel to the construction of design issues in reference to the central ideas fostered by the cybernetic model. It unpacks and explains this crucial relationship, in the work of digital architects, between the use of information technology in design and the conception of architectural problems around an informational ontology. This book will appeal to architecture students and scholars interested in understanding the recent transformations in the architectural landscape related to the advent of computer-based design paradigms.

This monograph investigates the stability and performance of control systems subject to actuator saturation. It presents new results obtained by both improving the treatment of the saturation function and constructing new Lyapunov functions. In particular, two improved treatments of the saturation function are described that exploit the intricate structural properties of its traditional convex hull representation. The authors apply these treatments to the estimation of the domain of attraction and the finite-gain L2 performance by using the quadratic Lyapunov function and the composite quadratic Lyapunov function. Additionally, an algebraic computation method is given for the exact determination of the maximal contractively invariant ellipsoid, a level set of a quadratic Lyapunov function. The authors conclude with a look at some of the problems that can be solved by the methods developed and described throughout the book. Numerous step-by-step descriptions, examples, and simulations are provided to illustrate the effectiveness of their results. Stability and Performance of Control Systems with Actuator Saturation will be an invaluable reference for graduate students, researchers, and practitioners in control engineering and applied mathematics.

The book reports on the latest advances in and applications of fractional order control and synchronization of chaotic systems, explaining the concepts involved in a clear, matter-of-fact style. It consists of 30 original contributions written by eminent scientists and active researchers in the field that address theories, methods and applications in a number of research areas related to fractional order control and synchronization of chaotic systems, such as: fractional chaotic systems, hyperchaotic systems, complex systems, fractional order discrete chaotic systems, chaos control, chaos synchronization, jerk circuits, fractional chaotic systems with hidden attractors, neural network, fuzzy logic controllers, behavioral modeling, robust and adaptive control, sliding mode control, different types of synchronization, circuit realization of chaotic systems, etc. In addition to providing readers extensive information on chaos fundamentals, fractional calculus, fractional differential equations, fractional control and stability, the book also discusses key applications of fractional order chaotic systems, as well as multidisciplinary solutions developed via control modeling. As such, it offers the perfect reference guide for graduate students, researchers and practitioners in the areas of fractional order control systems and fractional order chaotic systems.

This book presents a detailed study on fractional-order, set-point, weighted PID control strategies and the development of curve-fitting-based approximation techniques for fractional-order parameters. Furthermore, in all the cases, it includes the Scilab-based commands and functions for easy implementation and better understanding, and to appeal to a wide range of readers working with the software. The presented Scilab-based toolbox is the first toolbox for fractional-order systems developed in open-source software. The toolboxes allow time and frequency domains as well as stability analysis of the fractional-order systems and controllers. The book also provides real-time examples of the control of process plants using the developed fractional-order based PID control strategies and the approximation techniques. The book is of interest to readers in the areas of fractional-order controllers, approximation techniques, process modeling, control, and optimization, both in industry and academia. In industry, the book is particularly valuable in the areas of research and development (R&D) as well as areas where PID controllers suffice - and it should be noted that around 80% of low-level controllers in industry are PID based. The book is also useful where conventional PIDs are constrained, such as in industries where long-term delay and non-linearity are present. Here it can be used for the design of controllers for real-time processes. The book is also a valuable teaching and learning resource for undergraduate and postgraduate students.

Statistical modeling is a critical tool in scientific research. This book provides comprehensive explanations of the concepts and philosophy of statistical modeling, together with a wide range of practical and numerical examples. The authors expect this work to be of great value not just to statisticians but also to researchers and practitioners in various fields of research such as information science, computer science, engineering, bioinformatics, economics, marketing and environmental science. It 's a crucial area of study, as statistical models are used to understand phenomena with uncertainty and to determine the structure of complex systems. They re also used to control such systems, as well as to make reliable predictions in various natural and social science fields.

This book presents the proceedings of the International Conference "Stability, Control, Differential Games" (SCDG2019, September 16 - 20, 2019, Yekaterinburg, Russia), organized by the Krasovskii Institute of Mathematics and Mechanics of the Ural Branch of the Russian Academy of Sciences. Discussing the latest advances in the theory of optimal control, stability theory and differential games, it also demonstrates the application of new techniques and numerical algorithms to solve problems in robotics, mechatronics, power and energy systems, economics and ecology. Further, the book includes fundamental results in control theory, stability theory and differential games presented at the conference, as well as a number of chapters focusing on novel approaches in solving important applied problems in control and optimization. Lastly, it evaluates recent major accomplishments, and forecasts developments in various up-and-coming areas, such as hybrid systems, model predictive control, Hamilton-Jacobi equations and advanced estimation algorithms.

Understanding the latest capabilities in the cyber threat landscape as well as the cyber forensic challenges and approaches is the best way users and organizations can prepare for potential negative events. Adopting an experiential learning approach, this book describes how cyber forensics researchers, educators and practitioners can keep pace with technological advances, and acquire the essential knowledge and skills, ranging from IoT forensics, malware analysis, and CCTV and cloud forensics to network forensics and financial investigations. Given the growing importance of incident response and cyber forensics in our digitalized society, this book will be of interest and relevance to researchers, educators and practitioners in the field, as well as students wanting to learn about cyber forensics.

This book, which resulted from an intensive discourse between experts from several disciplines - complexity theorists, cognitive scientists, philosophers, urban planners and urban designers, as well as a zoologist and a physiologist - addresses various issues regarding cities. It is a first step in responding to the challenge of generating just such a discourse, based on a dilemma identified in the CTC (Complexity Theories of Cities) domain. The latter has demonstrated that cities exhibit the properties of natural, organic complex systems: they are open, complex and bottom-up, have fractal structures and are often chaotic. CTC have further shown that many of the mathematical formalisms and models developed to study material and organic complex systems also apply to cities. The dilemma in the current state of CTC is that cities differ from natural complex systems in that they are hybrid complex systems composed, on the one hand, of artifacts such as buildings, roads and bridges, and of natural human agents on the other. This raises a plethora of new questions on the difference between the natural and the artificial, the cognitive origin of human action and behavior, and the role of planning and designing cities. The answers to these questions cannot come from a single discipline; they must instead emerge from a discourse between experts from several disciplines engaged in CTC.

New Research in Information Behaviour, co-edited by Professor Amanda Spink and Dr. Jannica Heinstrom provides an understanding of the new directions, leading edge theories and models in information behaviour. Information behaviour is conceptualized as complex human information related processes that are embedded within an individual's everyday social and life processes. The book presents chapters by a range of scholars who show new research directions that often challenge the established views and paradigms of information behaviour studies. Beginning with an evolutionary framework, the book builds our understanding of information behaviours over various epochs of human existence from the Palaeolithic Era and within pre-literate societies, to contemporary behaviours by 21st century humans. Drawing upon social and psychological science theories the book presents a more integrated and holistic approach understanding of information behaviours. This book is directly relevant to information scientists, information professionals and librarians, social and evolutionary psychologists, social scientists and people interested in understanding more about their own information behaviours.

This book constitutes the refereed post-conference proceedings of the 4th International Conference on Intelligence Science, ICIS 2020, held in Durgapur, India, in February 2021 (originally November 2020). The 23 full papers and 4 short papers presented were carefully reviewed and selected from 42 submissions. One extended abstract is also included. They deal with key issues in brain cognition; uncertain theory; machine learning; data intelligence; language cognition; vision cognition; perceptual intelligence; intelligent robot; and medical artificial intelligence.

Chaos in science has always been a fascinating realm since it challenges the usual scientific approach of reductionism. While carefully distinguishing between complexity, holism, randomness, incompleteness, nondeterminism and stochastic behaviour the authors show that, although many aspects of chaos have been phenomenologically understood, most of its defining principles are still difficult to grasp and formulate. Demonstrating that chaos escapes all traditional methods of description, the authors set out to find new methods to deal with this phenomenon and illustrate their constructive approach with many examples from physics, biology and information technology. While maintaining a high level of rigour, an overly complicated mathematical apparatus is avoided in order to make this book accessible, beyond the specialist level, to a wider interdisciplinary readership.

The book provides an encompassing overview of all aspects relating to the sharing economy paradigm in different fields of study, and shows the ongoing research efforts in filling previously identified gaps in understanding in this area. Control and optimization analytics for the sharing economy explores bespoke analytics, tools, and business models that can be used to help design collaborative consumption services (the shared economy). It provides case studies of collaborative consumption in the areas of energy and mobility. The contributors review successful examples of sharing systems, and explore the theory for designing effective and stable shared-economy models. They discuss recent innovations in and uses of shared economy models in niche areas, such as energy and mobility. Readers learn the scientific challenging issues associated with the realization of a sharing economy. Conceptual and practical matters are examined, and the state-of-the-art tools and techniques to address such applications are explained. The contributors also show readers how topical problems in engineering, such as energy consumption in power grids, or bike sharing in transportation networks, can be formulated and solved from a general collaborative consumption perspective. Since the book takes a mathematical perspective to the topic, researchers in business, computer science, optimization and control find it useful. Practitioners also use the book as a point of reference, as it explores and investigates the analytics behind economy sharing.

What are the relations between the shape of a system of cities and that of fish school? Which events should happen in a cell in order that it participates to one of the finger of our hands? How to interpret the shape of a sand dune? This collective book written for the non-specialist addresses these questions and more generally, the fundamental issue of the emergence of forms and patterns in physical and living systems. It is a single book gathering the different aspects of morphogenesis and approaches developed in different disciplines on shape and pattern formation. Relying on the seminal works of D'Arcy Thompson, Alan Turing and Rene Thom, it confronts major examples like plant growth and shape, intra-cellular organization, evolution of living forms or motifs generated by crystals. A book essential to understand universal principles at work in the shapes and patterns surrounding us but also to avoid spurious analogies.

No pleasure lasts long unless there is variety in it. Publilius Syrus, Moral Sayings We've been very fortunate to receive fantastic feedback from our readers during the last four years, since the first edition of How to Solve It: Modern Heuristics was published in 1999. It's heartening to know that so many people appreciated the book and, even more importantly, were using the book to help them solve their problems. One professor, who published a review of the book, said that his students had given the best course reviews he'd seen in 15 years when using our text. There can be hardly any better praise, except to add that one of the book reviews published in a SIAM journal received the best review award as well. We greatly appreciate your kind words and personal comments that you sent, including the few cases where you found some typographical or other errors. Thank you all for this wonderful support.

The nucleus of this volume consists of a number of papers presented at the Advanced Research Workshop on liThe Impact of New Information Technologies on Library Management, Resources and Cooperation" , held in Luxembourg fran 19-23 November 1984. The oorkshop was a joint effort of four international organisations. The Scientific Affairs Division of the North .Atlantic Treaty Organization, through a personal canmitment and interest expressed by Dr. H. Durand, Assistant Secretary General for Scientific Affairs, was the first and major sponsor acting as a catalyst in enabling the Workshop to take place. Through its support for travel and subsistence costs of some of the North American participants, the Workshop could become a platfo~in for the exchange of ideas between parties concerned with information handling and transmission and information policy in Western Europe and North America. The Directorate General for Information Market and Innovation of the Canmission of the European Communities hosted the Vlorkshop in its facilities - the Jean l'bnnet Building in Luxembourg - also providing for simultaneous translation in the main languages of the European Community. Moreover, the Canmission generously funded the participation of key participants fran Community countries and provided participants with ample info~ination on existing Community programmes related to electronic publications, electronic transmission of documents, copyright problems, problems of standards, telecanmunication, and so on. 'I'he Council of Europe supported attendance fran Sweden, Austria and Spain. And lastly, the European Cultural Foundation organised the event on behalf of all these organisa tions.

30 years after its publication Marshall McLuhan's The Medium is the Massage remains his most entertaining, provocative, and piquant book. With every technological and social "advance" McLuhan's proclamation that "the media work us over completely" becomes more evident and plain. In his words, Uso pervasive are they in their personal, political, economic, aesthetic, psychological, moral, ethical and social consequences that they leave no part of us untouched, unaffected, or unaltered'. McLuhan's remarkable observation that "societies have always been shaped more by the nature of the media by which men communicate than by the content of the communication" is undoubtedly more relevant today than ever before. With the rise of the internet and the explosion of the digital revolution there has never been a better time to revisit Marshall McLuhan.

This book bridges the current gap between the theory of symmetry-based dynamics and its application to model and analyze complex systems. As an alternative approach, the authors use the symmetry of the system directly to formulate the appropriate models, and also to analyze the dynamics. Complex systems with symmetry arise in a wide variety of fields, including communication networks, molecular dynamics, manufacturing businesses, ecosystems, underwater vehicle dynamics, celestial and spacecraft dynamics and continuum mechanics. A general approach for their analysis has been to derive a detailed model of their individual parts, connect the parts and note that the system contains some sort of symmetry, then attempt to exploit this symmetry in order to simplify numerical computations. This approach can result in highly complicated models that are difficult to analyze even numerically. The alternative approach, while nonstandard, is not entirely new among the mathematics community. However, there is much less familiarity with the techniques of symmetry-breaking bifurcation, as they apply to the engineering, design and fabrication, of complex systems, in particular, nonlinear sensor devices with special emphasis on the conceptualization and development of new technologies of magnetic sensors such as fluxgate magnetometers and SQUID (Superconducting Quantum Interference Devices), E-- (electric-field) sensors, and communication and navigation systems that require multiple frequencies of operation, such as radar and antenna devices as well as gyroscopic systems.

This book presents a time-delay approach to the analysis and synthesis of networked control systems (NCSs) under communication constraints. Differently from other approaches, the time-delay approach to NCSs allows communication delays to be larger than the sampling intervals in the presence of scheduling protocols. The book starts from a comprehensive introduction to three main approaches to sampled-data and networked control. It then focuses on time-delay approach, and the modelling of the closed-loop systems in the form of time-delay system. It presents discontinuous (in time) Lyapunov functional constructions that are efficient for NCSs in the presence of communications delays. Further, it highlights time-delay approaches developed to model and analyze NCSs under communication constraints, with a particular focus on dynamic quantization, round-robin, try-once-discard and stochastic protocols. The results are first presented for the continuous-time NCSs and then extended to discrete-time NCSs. Discussing recent developments in Lyapunov-based analysis of NCSs under communication constraints, the book is a valuable resource for researchers interested in sampled-data and networked control, and time-delay systems, as well as for graduate students in automatic control and systems theory.

Engineering practice often has to deal with complex systems of multiple variable and multiple parameter models almost always with strong non-linear coupling. The conventional analytical techniques-based approaches for describing and predicting the behaviour of such systems in many cases are doomed to failure from the outset, even in the phase of the construction of a more or less appropriate mathematical model. These approaches normally are too categorical in the sense that in the name of modelling accuracy they try to describe all the structural details of the real physical system to be modelled. This can significantly increase the intricacy of the model and may result in a enormous computational burden without achieving considerable improvement of the solution. The best paradigm exemplifying this situation may be the classic perturbation theory: the less significant the achievable correction, the more work has to be invested to obtain it.

A further important component of machine intelligence is a kind of structural uniformity giving room and possibility to model arbitrary particular details a priori not specified and unknown. This idea is similar to the ready-to-wear industry, which introduced products, which can be slightly modified later on in contrast to tailor-made creations aiming at maximum accuracy from the beginning. These subsequent corrections can be carried out by machines automatically. This learning ability is a key element of machine intelligence.

The past decade confirmed that the view of typical components of the present soft computing as fuzzy logic, neural computing, evolutionary computation and probabilistic reasoning are of complementary nature and that the best results can be applied by their combined application.

Today, the two complementary branches of Machine Intelligence, that is, Artificial Intelligence and Computational Intelligence serve as the basis of Intelligent Engineering Systems. The huge number of scientific results published in Journal and conference proceedings worldwide substantiates this statement. The present book contains several articles taking different viewpoints in the field of intelligent systems. "

This textbook teaches students techniques for the design of advanced digital systems using System-on-Chip (SoC) Field Programmable Gate Arrays (FPGAs). The author demonstrates design of custom hardware components for the FPGA fabric using VHDL, with implementation of custom hardware-software interfaces. Readers gain hands-on experience by writing programs and Linux device drivers in C to interact with custom hardware. This textbook enables laboratory experience in the design of custom digital systems using SoC FPGAs, emphasizing computational tasks such as digital signal processing, audio, or video processing.

This book is an updated version of the information theory classic, first published in 1990. About one-third of the book is devoted to Shannon source and channel coding theorems; the remainder addresses sources, channels, and codes and on information and distortion measures and their properties.

New in this edition: Expanded treatment of stationary or sliding-block codes and their relations to traditional block codesExpanded discussion of results from ergodic theory relevant to information theoryExpanded treatment of B-processes -- processes formed by stationary coding memoryless sourcesNew material on trading off information and distortion, including the Marton inequalityNew material on the properties of optimal and asymptotically optimal source codesNew material on the relationships of source coding and rate-constrained simulation or modeling of random processes

Significant material not covered in other information theory texts includes stationary/sliding-block codes, a geometric view of information theory provided by process distance measures, and general Shannon coding theorems for asymptotic mean stationary sources, which may be neither ergodic nor stationary, and d-bar continuous channels.

This book provides step-by-step explanations of successful implementations and practical applications of machine learning. The book's GitHub page contains software codes to assist readers in adapting materials and methods for their own use. A wide variety of applications are discussed, including wireless mesh network and power systems optimization; computer vision; image and facial recognition; protein prediction; data mining; and data discovery. Numerous state-of-the-art machine learning techniques are employed (with detailed explanations), including biologically-inspired optimization (genetic and other evolutionary algorithms, swarm intelligence); Viola Jones face detection; Gaussian mixture modeling; support vector machines; deep convolutional neural networks with performance enhancement techniques (including network design, learning rate optimization, data augmentation, transfer learning); spiking neural networks and timing dependent plasticity; frequent itemset mining; binary classification; and dynamic programming. This book provides valuable information on effective, cutting-edge techniques, and approaches for students, researchers, practitioners, and teachers in the field of machine learning.

This book introduces to blockchain and deep learning and explores and illustrates the current and new trends that integrate them. The pace and speeds for connectivity are certain on the ascend. Blockchain and deep learning are twin technologies that are integral to integrity and relevance of network contents. Since they are data-driven technologies, rapidly growing interests exist to incorporate them in efficient and secure data sharing and analysis applications. Blockchain and deep learning are sentinel contemporary research technologies. This book provides a comprehensive reference for blockchain and deep learning by covering all important topics. It identifies the bedrock principles and forward projecting methodologies that illuminate the trajectory of developments for the decades ahead.

Originally published in 1995, Large Deviations for Performance Analysis consists of two synergistic parts. The first half develops the theory of large deviations from the beginning, through recent results on the theory for processes with boundaries, keeping to a very narrow path: continuous-time, discrete-state processes. By developing only what is needed for the applications, the theory is kept to a manageable level, both in terms of length and in terms of difficulty. Within its scope, the treatment is detailed, comprehensive and self-contained. As the book shows, there are sufficiently many interesting applications of jump Markov processes to warrant a special treatment. The second half is a collection of applications developed at Bell Laboratories. The applications cover large areas of the theory of communication networks: circuit switched transmission, packet transmission, multiple access channels, and the M/M/1 queue. Aspects of parallel computation are covered as well including, basics of job allocation, rollback-based parallel simulation, assorted priority queueing models that might be used in performance models of various computer architectures, and asymptotic coupling of processors. These applications are thoroughly analysed using the tools developed in the first half of the book.