This book introduces recent results on output synchronization of complex dynamical networks with single and multiple weights. It discusses novel research ideas and a number of definitions in complex dynamical networks, such as H-Infinity output synchronization, adaptive coupling weights, multiple weights, the relationship between output strict passivity and output synchronization. Furthermore, it methodically edits the research results previously published in various flagship journals and presents them in a unified form. The book is of interest to university researchers and graduate students in engineering and mathematics who wish to study output synchronization of complex dynamical networks.

In this volume cultural, social and cognitive influences on the research and teaching of mathematical modelling are explored from a variety of theoretical and practical perspectives. The authors of the current volume are all members of the International Community of Teachers of Mathematical Modelling and Applications, the peak research body in this field. A distinctive feature of this volume is the high number of authors from South American countries. These authors bring quite a different perspective to modelling than has been showcased in previous books in this series, in particular from a cultural point of view. As well as recent international research, there is a strong emphasis on pedagogical issues including those associated with technology and assessment, in the teaching and learning of modelling. Applications at various levels of education are exemplified. The contributions reflect common issues shared globally and represent emergent or on-going challenges.

This book presents the theoretical details and computational performances of algorithms used for solving continuous nonlinear optimization applications imbedded in GAMS. Aimed toward scientists and graduate students who utilize optimization methods to model and solve problems in mathematical programming, operations research, business, engineering, and industry, this book enables readers with a background in nonlinear optimization and linear algebra to use GAMS technology to understand and utilize its important capabilities to optimize algorithms for modeling and solving complex, large-scale, continuous nonlinear optimization problems or applications. Beginning with an overview of constrained nonlinear optimization methods, this book moves on to illustrate key aspects of mathematical modeling through modeling technologies based on algebraically oriented modeling languages. Next, the main feature of GAMS, an algebraically oriented language that allows for high-level algebraic representation of mathematical optimization models, is introduced to model and solve continuous nonlinear optimization applications. More than 15 real nonlinear optimization applications in algebraic and GAMS representation are presented which are used to illustrate the performances of the algorithms described in this book. Theoretical and computational results, methods, and techniques effective for solving nonlinear optimization problems, are detailed through the algorithms MINOS, KNITRO, CONOPT, SNOPT and IPOPT which work in GAMS technology.

The volume presents a selection of in-depth studies and state-of-the-art surveys of several challenging topics that are at the forefront of modern applied mathematics, mathematical modeling, and computational science. These three areas represent the foundation upon which the methodology of mathematical modeling and computational experiment is built as a ubiquitous tool in all areas of mathematical applications. This book covers both fundamental and applied research, ranging from studies of elliptic curves over finite fields with their applications to cryptography, to dynamic blocking problems, to random matrix theory with its innovative applications. The book provides the reader with state-of-the-art achievements in the development and application of new theories at the interface of applied mathematics, modeling, and computational science.

This book aims at fostering interdisciplinary collaborations required to meet the modern challenges of applied mathematics, modeling, and computational science. At the same time, the contributions combine rigorous mathematical and computational procedures and examples from applications ranging from engineering to life sciences, providing a rich ground for graduate student projects.

Combining control theory and modeling, this textbook introduces and builds on methods for simulating and tackling concrete problems in a variety of applied sciences. Emphasizing "learning by doing," the authors focus on examples and applications to real-world problems. An elementary presentation of advanced concepts, proofs to introduce new ideas, and carefully presented MATLAB(r) programs help foster an understanding of the basics, but also lead the way to new, independent research.

With minimal prerequisites and exercises in each chapter, this work serves as an excellent textbook and referencefor graduate and advanced undergraduatestudents, researchers, and practitioners in mathematics, physics, engineering, computer science, as well as biology, biotechnology, economics, and finance."

This book provides a generalised approach to fractal dimension theory from the standpoint of asymmetric topology by employing the concept of a fractal structure. The fractal dimension is the main invariant of a fractal set, and provides useful information regarding the irregularities it presents when examined at a suitable level of detail. New theoretical models for calculating the fractal dimension of any subset with respect to a fractal structure are posed to generalise both the Hausdorff and box-counting dimensions. Some specific results for self-similar sets are also proved. Unlike classical fractal dimensions, these new models can be used with empirical applications of fractal dimension including non-Euclidean contexts. In addition, the book applies these fractal dimensions to explore long-memory in financial markets. In particular, novel results linking both fractal dimension and the Hurst exponent are provided. As such, the book provides a number of algorithms for properly calculating the self-similarity exponent of a wide range of processes, including (fractional) Brownian motion and Levy stable processes. The algorithms also make it possible to analyse long-memory in real stocks and international indexes. This book is addressed to those researchers interested in fractal geometry, self-similarity patterns, and computational applications involving fractal dimension and Hurst exponent.

This contributed volume is based on talks given at the August 2016 summer school "Fluids Under Pressure," held in Prague as part of the "Prague-Sum" series. Written by experts in their respective fields, chapters explore the complex role that pressure plays in physics, mathematical modeling, and fluid flow analysis. Specific topics covered include: Oceanic and atmospheric dynamics Incompressible flows Viscous compressible flows Well-posedness of the Navier-Stokes equations Weak solutions to the Navier-Stokes equations Fluids Under Pressure will be a valuable resource for graduate students and researchers studying fluid flow dynamics.

This thesis demonstrates techniques that provide faster and more accurate solutions to a variety of problems in machine learning and signal processing. The author proposes a "greedy" algorithm, deriving sparse solutions with guarantees of optimality. The use of this algorithm removes many of the inaccuracies that occurred with the use of previous models.

Reliability and Safety of Complex Technical Systems and Processes offers a comprehensive approach to the analysis, identification, evaluation, prediction and optimization of complex technical systems operation, reliability and safety. Its main emphasis is on multistate systems with ageing components, changes to their structure, and their components reliability and safety parameters during the operation processes. Reliability and Safety of Complex Technical Systems and Processes presents integrated models for the reliability, availability and safety of complex non-repairable and repairable multistate technical systems, with reference to their operation processes and their practical applications to real industrial systems. The authors consider variables in different operation states, reliability and safety structures, and the reliability and safety parameters of components, as well as suggesting a cost analysis for complex technical systems. Researchers and industry practitioners will find information on a wide range of complex technical systems in Reliability and Safety of Complex Technical Systems and Processes. It may prove an easy-to-use guide to reliability and safety evaluations of real complex technical systems, both during their operation and at the design stages.

"The book of nature is written in the language of mathematics "-- "Galileo Galilei"

How is it possible to predict weather patterns for tomorrow, with access solely to today s weather data? And how is it possible to predict the aerodynamic behavior of an aircraft that has yet to be built?

The answer is computer simulations based on mathematical models sets of equations that describe the underlying physical properties. However, these equations are usually much too complicated to solve, either by the smartest mathematician or the largest supercomputer. This problem is overcome by constructing an approximation: a numerical model with a simpler structure can be translated into a program that tells the computer how to carry out the simulation.

This book conveys the fundamentals of mathematical models, numerical methods and algorithms. Opening with a tutorial on mathematical models and analysis, it proceeds to introduce the most important classes of numerical methods, with finite element, finite difference and spectral methods as central tools. The concluding section describes applications in physics and engineering, including wave propagation, heat conduction and fluid dynamics. Also covered are the principles of computers and programming, including MATLAB(r).

This volume provides a unique collection of mathematical tools and industrial case studies in digital manufacturing. It addresses various topics, ranging from models of single production technologies, production lines, logistics and workflows to models and optimization strategies for energy consumption in production. The digital factory represents a network of digital models and simulation and 3D visualization methods for the holistic planning, realization, control and ongoing improvement of all factory processes related to a specific product. In the past ten years, all industrialized countries have launched initiatives to realize this vision, sometimes also referred to as Industry 4.0 (in Europe) or Smart Manufacturing (in the United States). Its main goals are * reconfigurable, adaptive and evolving factories capable of small-scale production * high-performance production, combining flexibility, productivity, precision and zero defects * energy and resource efficiency in manufacturing None of these goals can be achieved without a thorough modeling of all aspects of manufacturing together with a multi-scale simulation and optimization of process chains; in other words, without mathematics. To foster collaboration between mathematics and industry in this area the European Consortium for Mathematics in Industry (ECMI) founded a special interest group on Math for the Digital Factory (M4DiFa). This book compiles a selection of review papers from the M4DiFa kick-off meeting held at the Weierstrass Institute for Applied Analysis and Stochastics in Berlin, Germany, in May 2014. The workshop aimed at bringing together mathematicians working on modeling, simulation and optimization with researchers and practitioners from the manufacturing industry to develop a holistic mathematical view on digital manufacturing. This book is of interest to practitioners from industry who want to learn about important mathematical concepts, as well as to scientists who want to find out about an exciting new area of application that is of vital importance for today's highly industrialized and high-wage countries.

Neuromechanics is a new, quickly growing field of neuroscience research that merges neurophysiology, biomechanics and motor control and aims at understanding living systems and their elements through interactions between their neural and mechanical dynamic properties. Although research in Neuromechanics is not limited by computational approaches, neuromechanical modeling is a powerful tool that allows for integration of massive knowledge gained in the past several decades in organization of motion related brain and spinal cord activity, various body sensors and reflex pathways, muscle mechanical and physiological properties and detailed quantitative morphology of musculoskeletal systems. Recent work in neuromechanical modeling has demonstrated advantages of such an integrative approach and led to discoveries of new emergent properties of neuromechanical systems. Neuromechanical Modeling of Posture and Locomotion will cover a wide range of topics from theoretical studies linking the organization of reflex pathways and central pattern generating circuits with morphology and mechanics of the musculoskeletal system (Burkholder; Nichols; Shevtsova et al.) to detailed neuromechanical models of postural and locomotor control (Bunderson; Edwards, Marking et al., Ting). Furthermore, uniquely diverse modeling approaches will be presented in the book including a theoretical dynamic analysis of locomotor phase transitions (Spardy and Rubin), a hybrid computational modeling that allows for in vivo interactions between parts of a living organism and a computer model (Edwards et al.), a physical neuromechanical model of the human locomotor system (Lewis), and others.

The book comprises contributions by some of the most respected scientists in the field of mathematical modeling and numerical simulation of the human cardiocirculatory system. It covers a wide range of topics, from the assimilation of clinical data to the development of mathematical and computational models, including with parameters, as well as their efficient numerical solution, and both in-vivo and in-vitro validation. It also considers applications of relevant clinical interest. This book is intended for graduate students and researchers in the field of bioengineering, applied mathematics, computer, computational and data science, and medicine wishing to become involved in the highly fascinating task of modeling the cardiovascular system.

This book presents the works and research findings of physicists, economists, mathematicians, statisticians, and financial engineers who have undertaken data-driven modelling of market dynamics and other empirical studies in the field of Econophysics. During recent decades, the financial market landscape has changed dramatically with the deregulation of markets and the growing complexity of products. The ever-increasing speed and decreasing costs of computational power and networks have led to the emergence of huge databases. The availability of these data should permit the development of models that are better founded empirically, and econophysicists have accordingly been advocating that one should rely primarily on the empirical observations in order to construct models and validate them. The recent turmoil in financial markets and the 2008 crash appear to offer a strong rationale for new models and approaches. The Econophysics community accordingly has an important future role to play in market modelling. The Econophys-Kolkata VIII conference proceedings are devoted to the presentation of many such modelling efforts and address recent developments. A number of leading researchers from across the globe report on their recent work, comment on the latest issues, and review the contemporary literature.

Features mathematical modeling techniques and real-world processes with applications in diverse fields Mathematical Modeling with Multidisciplinary Applications details the interdisciplinary nature of mathematical modeling and numerical algorithms. The book combines a variety of applications from diverse fields to illustrate how the methods can be used to model physical processes, design new products, find solutions to challenging problems, and increase competitiveness in international markets. Written by leading scholars and international experts in the field, the book presents new and emerging topics in areas including finance and economics, theoretical and applied mathematics, engineering and machine learning, physics, chemistry, ecology, and social science. In addition, the book thoroughly summarizes widely used mathematical and numerical methods in mathematical modeling and features: * Diverse topics such as partial differential equations (PDEs), fractional calculus, inverse problems by ordinary differential equations (ODEs), semigroups, decision theory, risk analysis, Bayesian estimation, nonlinear PDEs in financial engineering, perturbation analysis, and dynamic system modeling * Case studies and real-world applications that are widely used for current mathematical modeling courses, such as the green house effect and Stokes flow estimation * Comprehensive coverage of a wide range of contemporary topics, such as game theory, statistical models, and analytical solutions to numerical methods * Examples, exercises with select solutions, and detailed references to the latest literature to solidify comprehensive learning * New techniques and applications with balanced coverage of PDEs, discrete models, statistics, fractional calculus, and more Mathematical Modeling with Multidisciplinary Applications is an excellent book for courses on mathematical modeling and applied mathematics at the upper-undergraduate and graduate levels. The book also serves as a valuable reference for research scientists, mathematicians, and engineers who would like to develop further insights into essential mathematical tools.

This work examines the conflict between movements and regimes using dynamic mathematical modeling methods. Most of the deaths from political violence in the world in this century have not been caused by war, but by conflict between governments and dissenters. It is hoped that scholars will improve their understanding of these conflicts, and thus help to reduce the costs.

This edited monograph offers a summary of future mathematical methods supporting the recent energy sector transformation. It collects current contributions on innovative methods and algorithms. Advances in mathematical techniques and scientific computing methods are presented centering around economic aspects, technical realization and large-scale networks. Over twenty authors focus on the mathematical modeling of such future systems with careful analysis of desired properties and arising scales. Numerical investigations include efficient methods for the simulation of possibly large-scale interconnected energy systems and modern techniques for optimization purposes to guarantee stable and reliable future operations. The target audience comprises research scientists, researchers in the R&D field, and practitioners. Since the book highlights possible future research directions, graduate students in the field of mathematical modeling or electrical engineering may also benefit strongly.

This volume covers selected topics addressed and discussed during the workshop "PDE models for multi-agent phenomena," which was held in Rome, Italy, from November 28th to December 2nd, 2016. The content mainly focuses on kinetic equations and mean field games, which provide a solid framework for the description of multi-agent phenomena. The book includes original contributions on the theoretical and numerical study of the MFG system: the uniqueness issue and finite difference methods for the MFG system, MFG with state constraints, and application of MFG to market competition. The book also presents new contributions on the analysis and numerical approximation of the Fokker-Planck-Kolmogorov equations, the isotropic Landau model, the dynamical approach to the quantization problem and the asymptotic methods for fully nonlinear elliptic equations. Chiefly intended for researchers interested in the mathematical modeling of collective phenomena, the book provides an essential overview of recent advances in the field and outlines future research directions.

Nonlinear Modelling of High Frequency Financial Time Series Edited by Christian Dunis and Bin Zhou In the competitive and risky environment of today's financial markets, daily prices and models based upon low frequency price series data do not provide the level of accuracy required by traders and a growing number of risk managers. To improve results, more and more researchers and practitioners are turning to high frequency data. Nonlinear Modelling of High Frequency Financial Time Series presents the latest developments and views of leading international researchers and market practitioners, in modelling high frequency data in finance. Combining both nonlinear modelling and intraday data for financial markets, the editors provide a fascinating foray into this extremely popular discipline. This book evolves around four major themes. The first introductory section focuses on high frequency financial data. The second part examines the exact nature of the time series considered: several linearity tests are presented and applied and their modelling implications assessed. The third and fourth parts are dedicated to modelling and forecasting these financial time series.

This book on constrained optimization is novel in that it fuses these themes: * use examples to introduce general ideas; * engage the student in spreadsheet computation; * survey the uses of constrained optimization;. * investigate game theory and nonlinear optimization, * link the subject to economic reasoning, and * present the requisite mathematics. Blending these themes makes constrained optimization more accessible and more valuable. It stimulates the student's interest, quickens the learning process, reveals connections to several academic and professional fields, and deepens the student's grasp of the relevant mathematics. The book is designed for use in courses that focus on the applications of constrained optimization, in courses that emphasize the theory, and in courses that link the subject to economics.

This work is devoted to the late Ukrainian computer scientist V. M. Glushkov on the 90th anniversary of his birthday. Dr. Glushkov is known for his contribution to the world computer science and technology and this volume analyzes the ideas and paths of development of informatics formulated by him and demonstrate their important role in constructing computer technologies of basic research in the fields of applied mathematics, theories of computer programming and computing systems. A significant portion of the monograph is devoted to the elucidation of new results obtained in the field of mathematical modeling of complicated processes, creation of new methods for solving and investigating optimization problems in different statements and development of computer technologies for investigations in the field of economy, biology, medicine and information security in systems. The monograph will be of particular interest to informatics specialists and experts using methods of informatics and computer technologies to investigate complicated processes of different natures and developing new information technologies. It may also be useful for both graduate students and postgraduates specializing in Computer Science.

This volume has been divided into two parts: Geometry and Applications. The geometry portion of the book relates primarily to geometric flows, laminations, integral formulae, geometry of vector fields on Lie groups and osculation; the articles in the applications portion concern some particular problems of the theory of dynamical systems, including mathematical problems of liquid flows and a study of cycles for non-dynamical systems.

This Work is based on the second international workshop entitled "Geometry and Symbolic Computations," held on May 15-18, 2013 at the University of Haifa and is dedicated to modeling (using symbolic calculations) in differential geometry and its applications in fields such as computer science, tomography and mechanics. It is intended to create a forum for students and researchers in pure and applied geometry to promote discussion of modern state-of-the-art in geometric modeling using symbolic programs such as Maple and Mathematica(r), as well as presentation of new results."

This book is open access under a CC BY 4.0 license. This easy-to-read book introduces the basics of solving partial differential equations by means of finite difference methods. Unlike many of the traditional academic works on the topic, this book was written for practitioners. Accordingly, it especially addresses: the construction of finite difference schemes, formulation and implementation of algorithms, verification of implementations, analyses of physical behavior as implied by the numerical solutions, and how to apply the methods and software to solve problems in the fields of physics and biology.

Collecting together contributed lectures and mini-courses, this book details the research presented in a special semester titled "Geometric mechanics - variational and stochastic methods" run in the first half of 2015 at the Centre Interfacultaire Bernoulli (CIB) of the Ecole Polytechnique Federale de Lausanne. The aim of the semester was to develop a common language needed to handle the wide variety of problems and phenomena occurring in stochastic geometric mechanics. It gathered mathematicians and scientists from several different areas of mathematics (from analysis, probability, numerical analysis and statistics, to algebra, geometry, topology, representation theory, and dynamical systems theory) and also areas of mathematical physics, control theory, robotics, and the life sciences, with the aim of developing the new research area in a concentrated joint effort, both from the theoretical and applied points of view. The lectures were given by leading specialists in different areas of mathematics and its applications, building bridges among the various communities involved and working jointly on developing the envisaged new interdisciplinary subject of stochastic geometric mechanics.