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Books > Reference & Interdisciplinary > Communication studies > Information theory
This book contains advances on the theory and applications of time-delay systems with particular focus on interconnected systems. The methods for stability analysis and control design are based on time-domain and frequency-domain approaches, for continuous-time and sampled-data systems, linear and nonlinear systems. This volume is a valuable source of reference for control practitioners, graduate students, and scientists researching practical as well as theoretical solutions to a variety of control problems inevitably influenced by the presence of time delays. The contents are organized in three parts: Interconnected Systems analysis, Modeling and and Analysis for Delay systems, and Stabilization and Control Strategies for Delay Systems. This volume presents a selection of 19 contributions presented in the 4th DelSys Workshop which took place in Gif-sur-Yvette, France November 25-27, 2015.
This book presents special systems derived from industrial models, including the complex saturation nonlinear functions and the delay nonlinear functions. It also presents typical methods, such as the classical Liapunov and Integral Inequalities methods. Providing constructive qualitative and stability conditions for linear systems with saturated inputs in both global and local contexts, it offers practitioners more concise model systems for modern saturation nonlinear techniques, which have the potential for future applications. This book is a valuable guide for researchers and graduate students in the fields of mathematics, control, and engineering.
A "New York Times" Notable Book
This book reports on the latest findings concerning nonlinear control theory and applications. It presents novel work on several kinds of commonly encountered nonlinear time-delay systems, including those whose nonlinear terms satisfy high-order polynomial form or general nonlinear form, those with nonlinear input or a triangular structure, and so on. As such, the book will be of interest to university researchers, R&D engineers and graduate students in the fields of control theory and control engineering who wish to learn about the core principles, methods, algorithms, and applications of nonlinear time-delay systems.
The 1st edition of Tervo's "Practical Signals Theory with MATLAB Applications" offers an organized presentation around applications that introduces the actual behavior of specific signals and uses them to motivate presentation of mathematical concepts. The text sequences the presentation of the major transforms by their complexity to help visualize phenomena from an equation to develop intuition and learn to analyze signals by inspection. Furthermore the text provides examples and problems designed to use MATLAB, making presentation more in line with modern engineering practice. Key features include: actual signal behavior presented first, from which mathematical theory is derived (most competitors do the opposite); an integrated CT/DT coverage; MATLAB integrated throughout; extensive use of innovative applications in examples and problems; and an emphasis on developing student intuition via analysis by inspection.
In the era of self-taught developers and programmers, essential topics in the industry are frequently learned without a formal academic foundation. A solid grasp of data structures and algorithms (DSA) is imperative for anyone looking to do professional software development and engineering, but classes in the subject can be dry or spend too much time on theory and unnecessary readings. Regardless of your programming language background, Codeless Data Structures and Algorithms has you covered. In this book, author Armstrong Subero will help you learn DSAs without writing a single line of code. Straightforward explanations and diagrams give you a confident handle on the topic while ensuring you never have to open your code editor, use a compiler, or look at an integrated development environment. Subero introduces you to linear, tree, and hash data structures and gives you important insights behind the most common algorithms that you can directly apply to your own programs. Codeless Data Structures and Algorithms provides you with the knowledge about DSAs that you will need in the professional programming world, without using any complex mathematics or irrelevant information. Whether you are a new developer seeking a basic understanding of the subject or a decision-maker wanting a grasp of algorithms to apply to your projects, this book belongs on your shelf. Quite often, a new, refreshing, and unpretentious approach to a topic is all you need to get inspired. What You'll Learn Understand tree data structures without delving into unnecessary details or going into too much theory Get started learning linear data structures with a basic discussion on computer memory Study an overview of arrays, linked lists, stacks and queues Who This Book Is ForThis book is for beginners, self-taught developers and programmers, and anyone who wants to understand data structures and algorithms but don't want to wade through unnecessary details about quirks of a programming language or don't have time to sit and read a massive book on the subject. This book is also useful for non-technical decision-makers who are curious about how algorithms work.
Distributed Coordination Theory for Robot Teams develops control algorithms to coordinate the motion of autonomous teams of robots in order to achieve some desired collective goal. It provides novel solutions to foundational coordination problems, including distributed algorithms to make quadrotor helicopters rendezvous and to make ground vehicles move in formation along circles or straight lines. The majority of the algorithms presented in this book can be implemented using on-board cameras. The book begins with an introduction to coordination problems, such as rendezvous of flying robots, and modelling. It then provides a solid theoretical background in basic stability, graph theory and control primitives. The book discusses the algorithmic solutions for numerous distributed control problems, focusing primarily on flying robotics and kinematic unicycles. Finally, the book looks to the future, and suggests areas discussed which could be pursued in further research. This book will provide practitioners, researchers and students in the field of control and robotics new insights in distributed multi-agent systems.
This book commemorates Eric Goles's achievements in science and engineering. Eric Goles is one of the world leaders in the field of automata and complexity. His groundbreaking discoveries are in the theory and analysis of complex systems, particularly in the field of discrete systems dynamics such as neural networks, automata networks, majority networks, bootstrap percolation models, cellular automata, computational complexity theory, discrete mathematics, and theoretical computer science. Topics include cellular automata, complex networks, models of computation, expansive systems, sandpile automata, Penrose tilings, Boolean automata, models of infection, Fibonacci trees, dominos, reversible automata, and fungal automata. The chapters are authored by world leaders in computer science, physics, mathematics, and engineering. The book will be a pleasure to explore for readers from all walks of life, from undergraduate students to university professors, from mathematicians, computer scientists, and engineers to chemists and biologists.
This monograph explores the synchronization of large-scale, multi-agent dynamical systems in the presence of disturbances, delays, and time-varying networks. Drawing upon their extensive work in this area, the authors provide a thorough treatment of agents with higher-order dynamics, different classes of models for agents, and the underlying networks representing the agents' actions. The high technical level of their presentation and their rigorous mathematical approach make this a timely and valuable resource that will fill a gap in the existing literature. Divided into two sections, the first part of the book focuses on state synchronization of homogeneous multi-agent systems. The authors consider state synchronization by determining control strategies for both continuous- and discrete-time systems that achieve state synchronization under both full- and partial-state coupling. The chapters that follow examine multi-agent systems with both linear and nonlinear time-varying agents, input-delays for continuous- and discrete-time systems, and communication delays for continuous-time systems. The second part of the book is dedicated to regulated output synchronization of heterogeneous multi-agent systems with linear and nonlinear agents. Both sections of the book include performance considerations in H2- and H-infinity norms in the presence of external disturbances. Research on synchronization of multi-agent systems has been growing in popularity and is highly interdisciplinary, with applications to automobile systems, aerospace systems, multiple-satellite GPS and high-resolution satellite imagery, aircraft formations, highway traffic platooning, industrial process control with multiple processes, and more. Synchronization of Multi-Agent Systems in the Presence of Disturbances and Delays will therefore be of interest to upper-level graduate students, researchers, and engineers in industry working on interconnected dynamical systems.
With its intuitive yet rigorous approach to machine learning, this text provides students with the fundamental knowledge and practical tools needed to conduct research and build data-driven products. The authors prioritize geometric intuition and algorithmic thinking, and include detail on all the essential mathematical prerequisites, to offer a fresh and accessible way to learn. Practical applications are emphasized, with examples from disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology. Over 300 color illustrations are included and have been meticulously designed to enable an intuitive grasp of technical concepts, and over 100 in-depth coding exercises (in Python) provide a real understanding of crucial machine learning algorithms. A suite of online resources including sample code, data sets, interactive lecture slides, and a solutions manual are provided online, making this an ideal text both for graduate courses on machine learning and for individual reference and self-study.
This book demonstrates the unifying methods of generalized versions of Hilfer, Prabhakar and Hilfer-Prabhakar fractional calculi, and we establish related unifying fractional integral inequalities of the following types: Iyengar, Landau, Polya, Ostrowski, Hilbert-Pachpatte, Hardy, Opial, Csiszar's f-Divergence, self-adjoint operator and related to fuzziness. Our results are univariate and multivariate. This book's results are expected to find applications in many areas of pure and applied mathematics, especially in fractional inequalities and fractional differential equations. Other interesting applications can be in applied sciences like geophysics, physics, chemistry, economics and engineering. This book is appropriate for researchers, graduate students, practitioners and seminars of the above disciplines, also to be in all science and engineering libraries.
This book offers a unique compendium of the authors own research on the use of theoretical stability analysis, showing how to take advantage of local stability design and ultimate boundedness for practical robot control. It addresses researchers and postgraduate students dealing with control theory, particularly with nonlinear systems. Thanks to the numerous worked examples, it could also be used as a textbook in postgraduate courses.
Fascinating journey explores key concepts in information theory in terms of Conway's ""Game of Life"" program. Topics include the limits of knowledge, paradox of complexity, Maxwell's demon, Big Bang theory, and much more. 1985 edition.
Information is central to the evolution of biological complexity, a physical system relying on a continuous supply of energy. Biology provides superb examples of the consequent Darwinian selection of mechanisms for efficient energy utilisation. Genetic information, underpinned by the Watson-Crick base-pairing rules is largely encoded by DNA, a molecule uniquely adapted to its roles in information storage and utilisation.This volume addresses two fundamental questions. Firstly, what properties of the molecule have enabled it to become the predominant genetic material in the biological world today and secondly, to what extent have the informational properties of the molecule contributed to the expansion of biological diversity and the stability of ecosystems. The author argues that bringing these two seemingly unrelated topics together enables Schroedinger's What is Life?, published before the structure of DNA was known, to be revisited and his ideas examined in the context of our current biological understanding.
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.
'Bold, inspired and hopeful' Arianna Huffington, founder and CEO of Thrive Global 'Lucid and captivating' Max Tegmark, professor of physics at MIT and author of Life 3.0 A captivating memoir that chronicles one woman's mission to humanise technology and what she learns about humanity along the way. Now more than ever, we find ourselves unable to express our true feelings through technology. Whether it's a misunderstood text, an oversimplified emoji or a Skype call that leaves us feeling lonely, when most of our communication is carried out through tech, the result is a virtual world that's lacking our humanity - a society lacking in empathy. Rana el Kaliouby discovered this when she left Cairo, a newly-married, Muslim woman, to take up her place at Cambridge University to study computer science. Many thousands of miles from home, she began to develop systems to help her better connect with her family. She started to pioneer the new field of Emotional Intelligence (EI). She now runs her company, Affectiva (the industry-leader in this emerging field) that builds EI into our technology and develops systems that understand humans the way we understand one another. This is the fascinating story of her mission to humanise technology and what she learns about humanity along the way.
"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. 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. |
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