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This book presents a class of novel, self-learning, optimal control schemes based on adaptive dynamic programming techniques, which quantitatively obtain the optimal control schemes of the systems. It analyzes the properties identified by the programming methods, including the convergence of the iterative value functions and the stability of the system under iterative control laws, helping to guarantee the effectiveness of the methods developed. When the system model is known, self-learning optimal control is designed on the basis of the system model; when the system model is not known, adaptive dynamic programming is implemented according to the system data, effectively making the performance of the system converge to the optimum. With various real-world examples to complement and substantiate the mathematical analysis, the book is a valuable guide for engineers, researchers, and students in control science and engineering.

Dynamic programming. --- Nonlinear systems. --- Systems, Nonlinear --- Engineering. --- Computational intelligence. --- Vibration. --- Dynamical systems. --- Dynamics. --- Control engineering. --- Control. --- Computational Intelligence. --- Vibration, Dynamical Systems, Control. --- Control engineering --- Control equipment --- Control theory --- Engineering instruments --- Automation --- Programmable controllers --- Dynamical systems --- Kinetics --- Mathematics --- Mechanics, Analytic --- Force and energy --- Mechanics --- Physics --- Statics --- Cycles --- Sound --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- Construction --- Industrial arts --- Technology --- System theory --- Mathematical optimization --- Programming (Mathematics) --- Systems engineering --- Control and Systems Theory.

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This book discusses recent developments in mathematical programming and game theory, and the application of several mathematical models to problems in finance, games, economics and graph theory. All contributing authors are eminent researchers in their respective fields, from across the world. This book contains a collection of selected papers presented at the 2017 Symposium on Mathematical Programming and Game Theory at New Delhi during 9–11 January 2017. Researchers, professionals and graduate students will find the book an essential resource for current work in mathematical programming, game theory and their applications in finance, economics and graph theory. The symposium provides a forum for new developments and applications of mathematical programming and game theory as well as an excellent opportunity to disseminate the latest major achievements and to explore new directions and perspectives.

Programming (Mathematics) --- Game theory. --- Games, Theory of --- Theory of games --- Mathematical models --- Mathematics --- Mathematical programming --- Goal programming --- Algorithms --- Functional equations --- Mathematical optimization --- Operations research --- Mathematics. --- Mathematical optimization. --- Mathematical statistics. --- Game Theory, Economics, Social and Behav. Sciences. --- Optimization. --- Statistics and Computing/Statistics Programs. --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Simulation methods --- System analysis --- Math --- Science --- Statistical methods

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This book covers recent advances in image processing and imaging sciences from an optimization viewpoint, especially convex optimization with the goal of designing tractable algorithms. Throughout the handbook, the authors introduce topics on the most key aspects of image acquisition and processing that are based on the formulation and solution of novel optimization problems. The first part includes a review of the mathematical methods and foundations required, and covers topics in image quality optimization and assessment. The second part of the book discusses concepts in image formation and capture from color imaging to radar and multispectral imaging. The third part focuses on sparsity constrained optimization in image processing and vision and includes inverse problems such as image restoration and de-noising, image classification and recognition and learning-based problems pertinent to image understanding. Throughout, convex optimization techniques are shown to be a critically important mathematical tool for imaging science problems and applied extensively. Convex Optimization Methods in Imaging Science is the first book of its kind and will appeal to undergraduate and graduate students, industrial researchers and engineers and those generally interested in computational aspects of modern, real-world imaging and image processing problems.           Discusses recent developments in imaging science and provides tools for solving image processing and computer vision problems using convex optimization methods.          The reader is provided with the state of the art advancements in each imaging science problem that is covered and is directed to cutting edge theory and methods that should particularly help graduate students and young researchers in shaping their research.          Each chapter of the book covers a real-world imaging science problem while balancing both the theoretical and experimental aspects. The theoretical foundation of the problem is discussed thoroughly and then from a practical point of view, extensive validation and experiments are provided to enable the transition from theory to practice.          Topics of high current relevance are covered and include color and spectral imaging, dictionary learning for image classification and recovery, optimization and evaluation of image quality, sparsity constrained estimation for image processing and computer vision etc.        Provides insight on handling real-world imaging science problems that involve hard and non-convex objective functions through tractable convex optimization methods with the goal of providing a favorable performance-complexity trade-off. .

Computer science. --- Image processing. --- Computer Science. --- Image Processing and Computer Vision. --- Signal, Image and Speech Processing. --- Image processing --- Convex programming. --- Digital techniques. --- Programming (Mathematics) --- Digital image processing --- Digital electronics --- Computer vision. --- Machine vision --- Vision, Computer --- Artificial intelligence --- Pattern recognition systems --- Optical data processing. --- Signal processing. --- Speech processing systems. --- Computational linguistics --- Electronic systems --- Information theory --- Modulation theory --- Oral communication --- Speech --- Telecommunication --- Singing voice synthesizers --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- Processing, Signal --- Information measurement --- Signal theory (Telecommunication) --- Optical computing --- Visual data processing --- Bionics --- Electronic data processing --- Integrated optics --- Photonics --- Computers --- Optical equipment

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Model checking is a computer-assisted method for the analysis of dynamical systems that can be modeled by state-transition systems. Drawing from research traditions in mathematical logic, programming languages, hardware design, and theoretical computer science, model checking is now widely used for the verification of hardware and software in industry. The editors and authors of this handbook are among the world's leading researchers in this domain, and the 32 contributed chapters present a thorough view of the origin, theory, and application of model checking. In particular, the editors classify the advances in this domain and the chapters of the handbook in terms of two recurrent themes that have driven much of the research agenda: the algorithmic challenge, that is, designing model-checking algorithms that scale to real-life problems; and the modeling challenge, that is, extending the formalism beyond Kripke structures and temporal logic. The book will be valuable for researchers and graduate students engaged with the development of formal methods and verification tools. "This handbook is an authoritative, comprehensive description of the state of the art in model checking. It belongs on the bookshelf of every researcher and practitioner in computer-aided verification." [Moshe Y. Vardi, George Distinguished Service Professor in Computational Engineering, Rice University] "With chapters written by the world’s leading experts from academia and industry, this authoritative book on model checking should be on the shelf of every computer science graduate student and every hardware and software engineer. As the scale and complexity of digital systems grow, and they must work in the presence of uncertainty in the physical world, verification techniques such as model checking will become increasingly important to ensure system reliability, safety, and security." [Jeannette Wing, Corporate Vice President, Microsoft Research].

Computer science. --- Computer software --- Software engineering. --- Computers. --- Computer science --- Mathematical logic. --- Quality control. --- Reliability. --- Industrial safety. --- Computer Science. --- Theory of Computation. --- Software Engineering/Programming and Operating Systems. --- Mathematical Logic and Foundations. --- Mathematics of Computing. --- Performance and Reliability. --- Quality Control, Reliability, Safety and Risk. --- Reusability. --- Mathematics. --- Industrial accidents --- Industries --- Job safety --- Occupational hazards, Prevention of --- Occupational health and safety --- Occupational safety and health --- Prevention of industrial accidents --- Prevention of occupational hazards --- Safety, Industrial --- Safety engineering --- Safety measures --- Safety of workers --- Accidents --- System safety --- Dependability --- Trustworthiness --- Conduct of life --- Factory management --- Industrial engineering --- Reliability (Engineering) --- Sampling (Statistics) --- Standardization --- Quality assurance --- Quality of products --- Algebra of logic --- Logic, Universal --- Mathematical logic --- Symbolic and mathematical logic --- Symbolic logic --- Mathematics --- Algebra, Abstract --- Metamathematics --- Set theory --- Syllogism --- Computer mathematics --- Discrete mathematics --- Electronic data processing --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic brains --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Cybernetics --- Machine theory --- Calculators --- Cyberspace --- Computer software engineering --- Engineering --- Reusability of software --- Reusable code (Computer programs) --- Software reusability --- Software reengineering --- Generic programming (Computer science) --- Informatics --- Science --- Prevention --- Programming (Mathematics) --- ADP systems (Computer systems) --- Computing systems --- Systems, Computer --- Electronic systems --- Cyberinfrastructure --- Mathematical programming --- Goal programming --- Algorithms --- Functional equations --- Mathematical optimization --- Operations research --- Information theory. --- Logic, Symbolic and mathematical. --- Operating systems (Computers). --- System safety. --- Safety, System --- Safety of systems --- Systems safety --- Industrial safety --- Systems engineering --- Computer operating systems --- Computers --- Disk operating systems --- Systems software --- Communication theory --- Communication --- Operating systems --- Computer science—Mathematics. --- Computer software—Reusability.