Intelligent technical systems are networked, embedded systems incorporating real-time capacities that are able to interact with and adapt to their environments. These systems need innovative approaches in order to meet requirements like cost, size, power and memory consumption, as well as real-time compliance and security.

Intelligent Technical Systems covers different levels like multimedia systems, embedded programming, middleware platforms, sensor networks and autonomous systems and applications for intelligent engineering.

Each level is discussed by a set of original articles summarizing the state of the art and presenting a concrete application; they include a deep discussion of their model and explain all design decisions relevant to obtain a mature solution.

The future obviously matters to us. It is, after all, where we'll be spending the rest of our lives. We need some degree of foresight if we are to make effective plans for managing our affairs. Much that we would like to know in advance cannot be predicted. But a vast amount of successful prediction is nonetheless possible, especially in the context of applied sciences such as medicine, meteorology, and engineering. This book examines our prospects for finding out about the future in advance. It addresses questions such as why prediction is possible in some areas and not others; what sorts of methods and resources make successful prediction possible; and what obstacles limit the predictive venture.

Nicholas Rescher develops a general theory of prediction that encompasses its fundamental principles, methodology, and practice and gives an overview of its promises and problems. Predicting the future considers the anthropological and historical background of the predictive enterprise. It also examines the conceptual, epistemic, and ontological principles that set the stage for predictive efforts. In short, Rescher explores the basic features of the predictive situation and considers their broader implications in science, in philosophy, and in the management of our daily affairs.

For the Love of Cybernetics: Personal Narratives by Cyberneticians is a collection of personal accounts that offer unique insights into cybernetics via the personal journeys of nine individuals. For the authors in this collection, cybernetics is not their "area of interest"-it is how they think about what they do, and it is their practice. Ray Ison, Bruce Clarke, Frank Galuzska, Paul Pangaro, Klaus Krippendorff, Peter Tuddenham, Lucas Pawlik, Bernard Scott, and Jocelyn Chapman differ in their lineage, emphasis, and engagement with cybernetics. What they have in common is that they share the belief that cybernetics is not a tool to apply here and there, but a unifying way of seeing the world that transforms how we behave, thus increasing possibilities for positive systemic change. This book was originally published as a special issue of the journal, World Futures.

"Find it hard to extract and utilise valuable knowledge from the ever-increasing data deluge?" If so, this book will help, as it explores pattern recognition technology and its concomitant role in extracting useful information to build technical and business models to gain competitive industrial advantage.
*Based on first-hand experience in the practice of pattern recognition technology and its development and deployment for profitable application in Industry.
Phiroz Bhagat is often referred to as the pioneer of neural net and pattern recognition technology, and is uniquely qualified to write this book. He brings more than two decades of experience in the "real-world" application of cutting-edge technology for competitive advantage in industry.

Two wave fronts are upon us today: we are being bombarded by an enormous amount of data, and we are confronted by continually increasing technical and business advances.

Ideally, the endless stream of data should be one of our major assets. However, this potential asset often tends to overwhelm rather than enrich. Competitive advantage depends on our ability to extract and utilize nuggets of valuable knowledge and insight from this data deluge. The challenges that need to be overcome include the under-utilization of available data due to competing priorities, and the separate and somewhat disparate existing data systems that have difficulty interacting with each other.

Conventional approaches to formulating models are becoming progressively more expensive in time and effort. To impart a competitive edge, engineering science in the 21st century needs to augment traditional modelling processes by auto-classifying and self-organizing data; developing models directly from operating experience, and then optimizing the results to provide effective strategies and operating decisions. This approach has wide applicability; in areas ranging from manufacturing processes, product performance and scientific research, to financial and business fields.

This monograph explores pattern recognition technology, and its concomitant role in extracting useful knowledge to build technical and business models directly from data, and in optimizing the results derived from these models within the context of delivering competitive industrial advantage. It is not intended to serve as a comprehensive reference source on the subject. Rather, it is based on first-hand experience in the practice of this technology: its development and deployment for profitable application in industry.

The technical topics covered in the monograph will focus on the triad of technological areas that constitute the contemporary workhorses of successful industrial application of pattern recognition. These are: systems for self-organising data; data-driven modelling; and genetic algorithms as robust optimizers.
"Find it hard to extract and utilise valuable knowledge from the ever-increasing data deluge?" If so, this book will help, as it explores pattern recognition technology and its concomitant role in extracting useful information to build technical and business models to gain competitive industrial advantage.
Based on first-hand experience in the practice of pattern recognition technology and its development and deployment for profitable application in Industry.
Phiroz Bhagat is often referred to as the pioneer of neural net and pattern recognition technology, and is uniquely qualified to write this book. He brings more than two decades of experience in the "real-world" application of cutting-edge technology for competitive advantage in industry.

Offers Both Standard and Novel Approaches for the Modeling of SystemsExamines the Interesting Behavior of Particular Classes of Models Chaotic Modelling and Simulation: Analysis of Chaotic Models, Attractors and Forms presents the main models developed by pioneers of chaos theory, along with new extensions and variations of these models. Using more than 500 graphs and illustrations, the authors show how to design, estimate, and test an array of models. Requiring little prior knowledge of mathematics, the book focuses on classical forms and attractors as well as new simulation methods and techniques. Ideas clearly progress from the most elementary to the most advanced. The authors cover deterministic, stochastic, logistic, Gaussian, delay, Henon, Holmes, Lorenz, Roessler, and rotation models. They also look at chaotic analysis as a tool to design forms that appear in physical systems; simulate complicated and chaotic orbits and paths in the solar system; explore the Henon-Heiles, Contopoulos, and Hamiltonian systems; and provide a compilation of interesting systems and variations of systems, including the very intriguing Lotka-Volterra system. Making a complex topic accessible through a visual and geometric style, this book should inspire new developments in the field of chaotic models and encourage more readers to become involved in this rapidly advancing area.

Cyber and its related technologies such as the Internet was introduced to the world only in late 1980s, and today it is unimaginable to think of a life without it. Despite being ubiquitous, cyber technology is still seen as an enigma by many, mainly due to its rapid development and the high level of science involved. In addition to the existing complexities of the technology, the level of threat matrix surrounding the cyber domain further leads to various misconceptions and exaggerations. Cyber technology is the future, thus forcing us to understand this complex domain to survive and evolve as technological beings. To understand the enigma, the book analyzes and disentangles the issues related to cyber technology. The author unravels the threats that terrorize the cyber world and aims to decrypt its domain. It also presents the existing reality of cyber environment in India and charts out a few recommendations for enhancing the country's cyber security architecture. Further, the book delves into detailed analysis of various issues like hacking, dark web, cyber enabled terrorism and covert cyber capabilities of countries like the US and China. Please note: Taylor & Francis does not sell or distribute the Hardback in India, Pakistan, Nepal, Bhutan, Bangladesh and Sri Lanka

The present book includes a set of selected papers from the Fifth International Conf- ence on Informatics in Control Automation and Robotics (ICINCO 2008), held in Funchal, Madeira - Portugal, from 11 to 15 May 2008. The conference was organized in three simultaneous tracks: Intelligent Control Systems and Optimization, Robotics and Automation, and Systems Modeling, Signal Processing and Control. The book is based on the same structure. ICINCO 2008 received 392 paper submissions, from more than 50 different co- tries in all continents. From these, after a blind review process, only 33 where - cepted as full papers, of which 18 were selected for inclusion in this book, based on the classifications provided by the Program Committee. The selected papers reflect the interdisciplinary nature of the conference. The diversity of topics is an important feature of this conference, enabling an overall perception of several important sci- tific and technological trends. These high quality standards will be maintained and reinforced at ICINCO 2009, to be held in Milan, Italy, and in future editions of this conference.

New practical techniques for nonlinear system research and evaluation

Nonlinear Systems Techniques and Applications provides the most practical techniques currently available for analyzing and identifying nonlinear systems from random data measured at the input and output points of the nonlinear systems. These new techniques require only one-dimensional spectral functions that are much simpler to compute and apply than previous nonlinear procedures. The new results show when and how to replace a wide class of single-input/single-output nonlinear models with simpler equivalent multiple-input/single-output linear models. While other techniques are usually restricted to Gaussian data, the new techniques developed here apply to data with arbitrary probability, correlation, and spectral properties.

Numerous examples used in the book are based on the analysis of real physical data passing through real nonlinear systems in the fields of oceanography, automotive engineering, and biomedical research.

For practicing engineers and scientists involved in aerospace, automotive, biomedical, electrical, mechanical, oceanographic, and other activities concerned with nonlinear system analysis, Nonlinear Systems Techniques and Applications is the essential reference work in the field.

Vilfredo Pareto was one of the great systems theorists of the 20th century, embracing economics, psychology, sociology and politics. In this work, Michael McLure takes as his subject of study the rapport between Pareto's economic and sociological theories, and consequently illuminates the role of economics in public policy development. A central theme running through this book is the overarching role of the "mechanical analogy" in all of Pareto's work. Important aspects and implications of Pareto's work considered by the author include: relations between pure economic theory and general sociology; the problem of collective economic welfare; the juxtaposition of Pareto's political sociology to Buchanan's public choice/constitutional economics; Pareto and methodology; and implications for public policy and government

The expertise of a professional mathmatician and a theoretical engineer provides a fresh perspective of stability and stable oscillations. The current state of affairs in stability theory, absolute stability of control systems, and stable oscillations of both periodic and almost periodic discrete systems is presented, including many applications in engineering such as stability of digital filters, digitally controlled thermal processes, neurodynamics, and chemical kinetics. This book will be an invaluable reference source for those whose work is in the area of discrete dynamical systems, difference equations, and control theory or applied areas that use discrete time models.

Mapping Cyberspace is a ground-breaking geographic exploration and critical reading of cyberspace, and information and communication technologies. The book:
* provides an understanding of what cyberspace looks like and the social interactions that occur there
* explores the impacts of cyberspace, and information and communication technologies, on cultural, political and economic relations
* charts the spatial forms of virutal spaces
* details empirical research and examines a wide variety of maps and spatialisations of cyberspace and the information society
* has a related website at http://www.MappingCyberspace.com.
This book will be a valuable addition to the growing body of literature on cyberspace and what it means for the future.

This volume features recent development and techniques in evolution equations by renown experts in the field. Each contribution emphasizes the relevance and depth of this important area of mathematics and its expanding reach into the physical, biological, social, and computational sciences as well as into engineering and technology. The reader will find an accessible summary of a wide range of active research topics, along with exciting new results. Topics include: Impulsive implicit Caputo fractional q-difference equations in finite and infinite dimensional Banach spaces; optimal control of averaged state of a population dynamic model; structural stability of nonlinear elliptic p(u)-Laplacian problem with Robin-type boundary condition; exponential dichotomy and partial neutral functional differential equations, stable and center-stable manifolds of admissible class; global attractor in Alpha-norm for some partial functional differential equations of neutral and retarded type; and more. Researchers in mathematical sciences, biosciences, computational sciences and related fields, will benefit from the rich and useful resources provided. Upper undergraduate and graduate students may be inspired to contribute to this active and stimulating field.

This book is devoted to the development of optimal control theory for finite dimensional systems governed by deterministic and stochastic differential equations driven by vector measures. The book deals with a broad class of controls, including regular controls (vector-valued measurable functions), relaxed controls (measure-valued functions) and controls determined by vector measures, where both fully and partially observed control problems are considered. In the past few decades, there have been remarkable advances in the field of systems and control theory thanks to the unprecedented interaction between mathematics and the physical and engineering sciences. Recently, optimal control theory for dynamic systems driven by vector measures has attracted increasing interest. This book presents this theory for dynamic systems governed by both ordinary and stochastic differential equations, including extensive results on the existence of optimal controls and necessary conditions for optimality. Computational algorithms are developed based on the optimality conditions, with numerical results presented to demonstrate the applicability of the theoretical results developed in the book. This book will be of interest to researchers in optimal control or applied functional analysis interested in applications of vector measures to control theory, stochastic systems driven by vector measures, and related topics. In particular, this self-contained account can be a starting point for further advances in the theory and applications of dynamic systems driven and controlled by vector measures.

Modern Statistical, Systems, and GPSS Simulation, Second Edition introduces the theory and implementation of discrete-event simulation. This text:
o establishes a theoretical basis for simulation methodology
o provides details of an important simulation language (GPSS - General Purpose Simulation System)
o integrates these two elements in a systems simulation case study
Valuable additions to the second edition include coverage of random number generators with astronomic period, new entropy-based tests of uniformity, gamma variate generation, results on the GLD, and variance reduction techniques.
GPSS/PC is an interactive implementation of GPSS for the IBM-PC compatible family of microcomputers. The disk accompanying Modern Statistical, Systems, and GPSS Simulation contains the limited educational version of GPSS/PC with many illustrative examples discussed in the text.

This book addresses a key technology for digital information processing: Kalman filtering, which is generally considered to be one of the greatest discoveries of the 20th century. It introduces readers to issues concerning various uncertainties in a single plant, and to corresponding solutions based on adaptive estimation. Further, it discusses in detail the issues that arise when Kalman filtering technology is applied in multi-sensor systems and/or multi-agent systems, especially when various sensors are used in systems like intelligent robots, autonomous cars, smart homes, smart buildings, etc., requiring multi-sensor information fusion techniques. Furthermore, when multiple agents (subsystems) interact with one another, it produces coupling uncertainties, a challenging issue that is addressed here with the aid of novel decentralized adaptive filtering techniques.Overall, the book's goal is to provide readers with a comprehensive investigation into the challenging problem of making Kalman filtering work well in the presence of various uncertainties and/or for multiple sensors/components. State-of-art techniques are introduced, together with a wealth of novel findings. As such, it can be a good reference book for researchers whose work involves filtering and applications; yet it can also serve as a postgraduate textbook for students in mathematics, engineering, automation, and related fields.To read this book, only a basic grasp of linear algebra and probability theory is needed, though experience with least squares, navigation, robotics, etc. would definitely be a plus.

This second edition comprehensively presents important tools of linear systems theory, including differential and difference equations, Laplace and Z transforms, and more.
Linear Systems Theory discusses:
Nonlinear and linear systems in the state space form and through the transfer function method
Stability, including marginal stability, asymptotical stability, global asymptotical stability, uniform stability, uniform exponential stability, and BIBO stability
Controllability
Observability
Canonical forms
System realizations and minimal realizations, including state space approach and transfer function realizations
System design
Kalman filters
Nonnegative systems
Adaptive control
Neural networks
The book focuses mainly on applications in electrical engineering, but it provides examples for most branches of engineering, economics, and social sciences.
What's New in the Second Edition?
Case studies drawn mainly from electrical and mechanical engineering applications, replacing many of the longer case studies
Expanded explanations of both linear and nonlinear systems as well as new problem sets at the end of each chapter
Illustrative examples in all the chapters
An introduction and analysis of new stability concepts
An expanded chapter on neural networks, analyzing advances that have occurred in that field since the first edition
Although more mainstream than its predecessor, this revision maintains the rigorous mathematical approach of the first edition, providing fast, efficient development of the material.
Linear Systems Theory enables its reader to develop his or her capabilities for modeling dynamic phenomena, examining their properties, and applying them to real-life situations.

This book bridges the gap between advances in the communities of computer science and physics--namely machine learning and statistical physics. It contains diverse but relevant topics in statistical physics, complex systems, network theory, and machine learning. Examples of such topics are: predicting missing links, higher-order generative modeling of networks, inferring network structure by tracking the evolution and dynamics of digital traces, recommender systems, and diffusion processes. The book contains extended versions of high-quality submissions received at the workshop, Dynamics On and Of Complex Networks (doocn.org), together with new invited contributions. The chapters will benefit a diverse community of researchers. The book is suitable for graduate students, postdoctoral researchers and professors of various disciplines including sociology, physics, mathematics, and computer science.

This book represents the best of the first three years of the Society for Chaos Theory in Psychology conferences. While chaos theory has been a topic of considerable interest in the physical and biological sciences, its applications in psychology and related fields have been obscured until recently by its complexity. Nevertheless, a small but rapidly growing community of psychologists, neurobiologists, sociologists, mathematicians, and philosophers have been coming together to discuss its implications and explore its research possibilities.
Chaos theory has been termed the first authentic paradigm shift since the advent of quantum physics. Whether this is true or not, it unquestionably bears profound implications for many fields of thought. These include the cognitive analysis of the mind, the nature of personality, the dynamics of psychotherapy and counseling, understanding brain events and behavioral records, the dynamics of social organization, and the psychology of prediction. To each of these topics, chaos theory brings the perspective of dynamic self-organizing processes of exquisite complexity. Behavior, the nervous system, and social processes exhibit many of the classical characteristics of chaotic systems -- they are deterministic and globally predictable and yet do not submit to precise predictability.
This volume is the first to explore ideas from chaos theory in a broad, psychological perspective. Its introduction, by the prominent neuroscientist Walter Freeman, sets the tone for diverse discussions of the role of chaos theory in behavioral research, the study of personality, psychotherapy and counseling, mathematical cognitive psychology, social organization, systems philosophy, and the understanding of the brain.

This book presents a new approach for the analysis of chaotic behavior in non-linear dynamical systems, in which output can be represented in quaternion parametrization. It offers a new family of methods for the analysis of chaos in the quaternion domain along with extensive numerical experiments performed on human motion data and artificial data. All methods and algorithms are designed to allow detection of deterministic chaos behavior in quaternion data representing the rotation of a body in 3D space. This book is an excellent reference for engineers, researchers, and postgraduate students conducting research on human gait analysis, healthcare informatics, dynamical systems with deterministic chaos or time series analysis.

With the advent of the National Curriculum, computer based modelling (CBM) is now a compulsory part of the school curriculum. Teachers are increasingly being encouraged to seek out opportunities for CBM in their own subject and across the curriculum. The new demands on the curriculum have left eachers and teacher trainers concerned as to their lack of experience in the area. This book sets out to provide a comprehensive guide to the area through an examination of a number of funded projects on CBM and their application to the school curriculum, setting them in the context of wider theoretical and practical concerns. It is acknowledged that computers bring about change in the classroom, both in teachers' professional development and innovative practices in teaching and learning. In highlighting how CBM can aid in the effective delivery of the curriculum, this book should be essential reading for teachers and researchers in the field.

Neural Network Modeling offers a cohesive approach to the statistical mechanics and principles of cybernetics as a basis for neural network modeling. It brings together neurobiologists and the engineers who design intelligent automata to understand the physics of collective behavior pertinent to neural elements and the self-control aspects of neurocybernetics. The theoretical perspectives and explanatory projections portray the most current information in the field, some of which counters certain conventional concepts in the visualization of neuronal interactions.

This book gives an in-depth introduction to the areas of modeling, identification, simulation, and optimization. These scientific topics play an increasingly dominant part in many engineering areas such as electrotechnology, mechanical engineering, aerospace, and physics. This book represents a unique and concise treatment of the mutual interactions among these topics.
Techniques for solving general nonlinear optimization problems as they arise in identification and many synthesis and design methods are detailed. The main points in deriving mathematical models via prior knowledge concerning the physics describing a system are emphasized. Several chapters discuss the identification of black-box models. Simulation is introduced as a numerical tool for calculating time responses of almost any mathematical model. The last chapter covers optimization, a generally applicable tool for formulating and solving many engineering problems.

This book deals with the simulation of the mechanical behavior of engineering structures, mechanisms and components. It presents a set of strategies and tools for formulating the mathematical equations and the methods of solving them using MATLAB. For the same mechanical systems, it also shows how to obtain solutions using a different approaches. It then compares the results obtained with the two methods. By combining fundamentals of kinematics and dynamics of mechanisms with applications and different solutions in MATLAB of problems related to gears, cams, and multilink mechanisms, and by presenting the concepts in an accessible manner, this book is intended to assist advanced undergraduate and mechanical engineering graduate students in solving various kinds of dynamical problems by using methods in MATLAB. It also offers a comprehensive, practice-oriented guide to mechanical engineers dealing with kinematics and dynamics of several mechanical systems.

Containing 71 articles, "Supplementary Volume 2," provides an up-to-date review of recent developments in the field of systems and control. New developments covered include: 'fuzzy logic control', 'neural nets in control systems' and 'robust stability and robust stable control'. "Supplementary Volume 2" also provides coverage of the theory and application of systems in specific areas: modelling and simulation, traffic control and biological systems and measurement and software engineering. This update will continue to provide the practising scientist and engineer with an invaluable reference source on topics in the field of systems and control.