This book develops a clear and systematic treatment of time series of data, regular and chaotic, that one finds in observations of nonlinear systems. The reader is led from measurements of one or more variables through the steps of building models of the source as a dynamical system, classifying the source by its dynamical characteristics, and finally predicting and controlling the dynamical system. The text examines methods for separating the signal of physical interest from contamination by unwanted noise, and for investigating the phase space of the chaotic signal and its properties. The emphasis throughout is on the use of the modern mathematical tools for investigating chaotic behavior to uncover properties of physical systems. The methods require knowledge of dynamical systems at the advanced undergraduate level and some knowledge of Fourier transforms and other signal processing methods. The toolkit developed in the book will provide the reader with efficient and effective methods for analyzing signals from nonlinear sources; these methods are applicable to problems of control, communication, and prediction in a wide variety of systems encountered in physics, chemistry, biology, and geophysics.

Asymptotic methods are of great importance for practical applications, especially in dealing with boundary value problems for small stochastic perturbations. This book deals with nonlinear dynamical systems perturbed by noise. It addresses problems in which noise leads to qualitative changes, escape from the attraction domain, or extinction in population dynamics. The most likely exit point and expected escape time are determined with singular perturbation methods for the corresponding Fokker-Planck equation. The authors indicate how their techniques relate to the Ito calculus applied to the Langevin equation. The book will be useful to researchers and graduate students.

This book is of interest to researchers inquiring about modern topics and methods in the kinematics, control and design of robotic manipulators. It considers the full range of robotic systems, including serial, parallel and cable driven manipulators, both planar and spatial. The systems range from being less than fully mobile to kinematically redundant to overconstrained. In addition to recognized areas, this book also presents recent advances in emerging areas such as the design and control of humanoids and humanoid subsystems, and the analysis, modeling and simulation of human body motions, as well as the mobility analysis of protein molecules and the development of machines which incorporate man.

The articles in this volume cover power system model reduction, transient and voltage stability, nonlinear control, robust stability, computation and optimization and have been written by some of the leading researchers in these areas. This book should be of interest to power and control engineers, and applied mathematicians.

This volume presents the lectures given by distinguishyed contributors at the First German-Polish Max Born Symposium, held at Wojnowice in Poland in September, 1991. This is the first such symposium to continue the tradition of a German-Polish collaboration in theoretical physics in the form of biannual seminars organized between the Universities of Leipzig and Wroclaw since the early seventies. The papers in this volume are devoted to quantum group theory, non-commutative differential geometry, and integrable systems. Particular emphasis is given to the formalisms of noncommutative geometry on quantum groups, the quantum deformation of Poincare algebra and the axiomatric approach to superselection rules. Possible relations between noncommutative geometry and particle phyics models are also considered. For researchers and postgraduate students of theoretical and mathematical physics.

This book comprises selected peer-reviewed proceedings of the International Conference on Applications of Fluid Dynamics (ICAFD 2018) organized by the School of Advanced Sciences, Vellore Institute of Technology, India, in association with the University of Botswana and the Society for Industrial and Applied Mathematics (SIAM), USA. With an aim to identify the existing challenges in the area of applied mathematics and mechanics, the book emphasizes the importance of establishing new methods and algorithms to address these challenges. The topics covered include diverse applications of fluid dynamics in aerospace dynamics and propulsion, atmospheric sciences, compressible flow, environmental fluid dynamics, control structures, viscoelasticity and mechanics of composites. Given the contents, the book is a useful resource for students, researchers as well as practitioners.

FEM updating allows FEMs to be tuned better to reflect measured data. It can be conducted using two different statistical frameworks: the maximum likelihood approach and Bayesian approaches. This book applies both strategies to the field of structural mechanics, using vibration data. Computational intelligence techniques including: multi-layer perceptron neural networks; particle swarm and GA-based optimization methods; simulated annealing; response surface methods; and expectation maximization algorithms, are proposed to facilitate the updating process. Based on these methods, the most appropriate updated FEM is selected, a problem that traditional FEM updating has not addressed. This is found to incorporate engineering judgment into finite elements through the formulations of prior distributions. Case studies, demonstrating the principles test the viability of the approaches, and. by critically analysing the state of the art in FEM updating, this book identifies new research directions.

In this volume the investigations of filtering problems, a start on which has been made in 55], are being continued and are devoted to theoretical problems of processing stochastic fields. The derivation of the theory of processing stochastic fields is similar to that of the theory extensively developed for stochastic processes ('stochastic fields with a one-dimensional domain'). Nevertheless there exist essential distinctions between these cases making a construction of the theory for the multi-dimensional case in such a way difficult. Among these are the absence of the notion of the 'past-future' in the case of fields, which plays a fundamental role in constructing stochastic processes theory. So attempts to introduce naturally the notion of the causality (non-anticipativity) when synthesising stable filters designed for processing fields have not met with success. Mathematically, principal distinctions between multi-dimensional and one-dimensional cases imply that the set of roots of a multi-variable polyno mial does not necessary consist of a finite number of isolated points. From the main theorem of algebra it follows that in the one-dimensional case every poly nomial of degree n has just n roots (considering their multiplicity) in the com plex plane. As a consequence, in particular, an arbitrary rational function cents(."

Approach your problems from the right It isn't that they can't see the solution. end and begin with the answers. Then It is that they can't see the problem. one day, perhaps you will find the final question. G.K. Chesterton. The Scandal of Father Brown 'The Point of a Pin'. 'The Hermit Clad in Crane Feathers' in R.van Gulik's The Chinese Maze Murders. Growing specialization and diversification have brought a host of monographs and textbooks on increasingly specialized topics. However, the "tree" of knowledge of mathematics and related fields does not grow only by putting forth new branches. It also happens, quite often in fact, that branches which were thought to be completely disparate are suddenly seen to be related. Further, the kind and level of sophistication of mathematics applied in various sciences has changed drastically in recent years: measure theory is used (non-trivially) in - gional and theoretical economics; algebraic geometry interacts with physics; the Minkowsky lemma, coding theory and the structure of water meet one another in pack ing and covering theory; quantum fields, crystal defects and mathematical programming profit from homotopy theory; Lie algebras are relevant to filtering; and prediction and electrical engineering can use Stein spaces. And in addition to this there are such new emerging subdisciplines as "completely integrable systems," "chaos, synergetics and large-scale order," which are almost impossible to fit into the existing classification schemes. They draw upon widely different sections of mathematics."

very small domain (environment) affects through analytic continuation the whole of Riemann surface, or analytic manifold . Riemann was a master at applying this principle and also the first who noticed and emphasized that a meromorphic function is determined by its 'singularities'. Therefore he is rightly regarded as the father of the huge 'theory of singularities' which is developing so quickly and whose importance (also for physics) can hardly be overe~timated. Amazing and mysterious for our cognition is the role of Euclidean space. Even today many philosophers believe (following Kant) that 'real space' is Euclidean and other spaces being 'abstract constructs of mathematicians, should not be called spaces'. The thesis is no longer tenable - the whole of physics testifies to that. Nevertheless, there is a grain of truth in the 3 'prejudice': E (three-dimensional Euclidean space) is special in a particular way pleasantly familiar to us - in it we (also we mathematicians!) feel particularly 'confident' and move with a sense of greater 'safety' than in non-Euclidean spaces. For this reason perhaps, Riemann space M stands out among the multitude of 'interesting geometries'. For it is: 1. Locally Euclidean, i. e. , M is a differentiable manifold whose tangent spaces TxM are equipped with Euclidean metric Uxi 2. Every submanifold M of Euclidean space E is equipped with Riemann natural metric (inherited from the metric of E) and it is well known how often such submanifolds are used in mechanics (e. g. , the spherical pendulum).

The world we live in is pervaded with uncertainty and imprecision. Is it likely to rain this afternoon? Should I take an umbrella with me? Will I be able to find parking near the campus? Should I go by bus? Such simple questions are a c- mon occurrence in our daily lives. Less simple examples: What is the probability that the price of oil will rise sharply in the near future? Should I buy Chevron stock? What are the chances that a bailout of GM, Ford and Chrysler will not s- ceed? What will be the consequences? Note that the examples in question involve both uncertainty and imprecision. In the real world, this is the norm rather than exception. There is a deep-seated tradition in science of employing probability theory, and only probability theory, to deal with uncertainty and imprecision. The mon- oly of probability theory came to an end when fuzzy logic made its debut. H- ever, this is by no means a widely accepted view. The belief persists, especially within the probability community, that probability theory is all that is needed to deal with uncertainty. To quote a prominent Bayesian, Professor Dennis Lindley, "The only satisfactory description of uncertainty is probability.

Engineers and mathematicians from European corporations and universities trade problems and solution techniques in creating mathematical models of the influence of road conditions on the behavior of vehicles (by which they mean automobiles). A dozen papers, reproduced from typescripts of varying rea

This book examines various mathematical toolsa "based on generalized collocation methodsa "to solve nonlinear problems related to partial differential and integro-differential equations. Covered are specific problems and models related to vehicular traffic flow, population dynamics, wave phenomena, heat convection and diffusion, transport phenomena, and pollution.

Based on a unified approach combining modeling, mathematical methods, and scientific computation, each chapter begins with several examples and problems solved by computational methods; full details of the solution techniques used are given. The last section of each chapter provides problems and exercises giving readers the opportunity to practice using the mathematical tools already presented. Rounding out the work is an appendix consisting of scientific programs in which readers may find practical guidelines for the efficient application of the collocation methods used in the book. Although the authors make use of MathematicaA(R), readers may use other packages such as MATLABA(R) or MapleTM depending on their specific needs and software preferences.

Generalized Collocation Methods is written for an interdisciplinary audience of graduate students, engineers, scientists, and applied mathematicians with an interest in modeling real-world systems by differential or operator equations. The work may be used as a supplementary textbook in graduate courses on modeling and nonlinear differential equations, or as a self-study handbook for researchers and practitioners wishing to expand their knowledge of practical solution techniques for nonlinear problems.

Because of its potential to "predict the unpredictable," Extreme Value Theory (EVT) and its methodology are currently in the spotlight. EVT affords some insight into extreme tails and maxima where standard models have proved unreliable. This is achieved with semi-parametric models which only specify the distributional shapes of maxima or of extreme tails. The rationale for these models are very basic limit and stability arguments.

Bringing together world-recognized authorities, Extreme Values in Finance, Telecommunications, and the Environment puts to rest some of the myths and misconceptions of EVT. It explores the application, use, and theory of extreme values in the areas of finance, insurance, the environment, and telecommunications. The book reviews the way in which this paradigm can answer questions in climatology, insurance, and finance, covers parts of univariate extreme values theory, and discusses estimation, diagnostics, and multivariate extremes. It presents issues in data network modeling and examines aspects of Value-at-Risk (VaR) and its estimation based on EVT. The final chapter gives an overview of multivariate extreme value distributions and the problem of measuring extremal dependencies.

Considered one of the hottest ideas in risk management, EVT is designed to allow anyone faced with calculating risky situations to determine the chances of being hit with one or even multiple catastrophic events. It provides a statistical methodology for dealing with the prediction of events which are so rare that they appear impossible. Presenting information from the forefront of knowledge and research, Extreme Values in Finance, Telecommunications, and the Environment brings you up to speed on current issues and techniques in EVT.

This book presents a collection of papers presented at the 3rd World Congress on Integrated Computational Materials Engineering (ICME), a specialty conference organized by The Minerals, Metals & Materials Society (TMS). This meeting convened ICME stakeholders to examine topics relevant to the global advancement of ICME as an engineering discipline. The papers presented in these proceedings are divided into six sections: (1) ICME Applications; (2) ICME Building Blocks; (3) ICME Success Stories and Applications (4) Integration of ICME Building Blocks: Multi-scale Modeling; (5) Modeling, Data and Infrastructure Tools, and (6) Process Optimization. . These papers are intended to further the global implementation of ICME, broaden the variety of applications to which ICME is applied, and ultimately help industry design and produce new materials more efficiently and effectively.

This book is intended to be an exhaustive study on regularity and other properties of continuity for different types of non-additive multimeasures and with respect to different types of topologies. The book is addressed to graduate and postgraduate students, teachers and all researchers in mathematics, but not only. Since the notions and results offered by this book are closely related to various notions of the theory of probability, this book will be useful to a wider category of readers, using multivalued analysis techniques in areas such as control theory and optimization, economic mathematics, game theory, decision theory, etc. Measure and integration theory developed during the early years of the 20th century is one of the most important contributions to modern mathematical analysis, with important applications in many fields. In the last years, many classical problems from measure theory have been treated in the non-additive case and also extended in the set-valued case. The property of regularity is involved in many results of mathematical analysis, due to its applications in probability theory, stochastic processes, optimal control problems, dynamical systems, Markov chains, potential theory etc.

Comprising specially selected papers on the subject of Computational Methods and Experimental Measurements, this book includes research from scientists, researchers and specialists who perform experiments, develop computer codes and carry out measurements on prototypes. Improvements relating to computational methods have generated an ever-increasing expansion of computational simulations that permeate all fields of science and technology. Validating the results of these improvements can be achieved by carrying out committed and accurate experiments, which have undertaken continuous development. Current experimental techniques have become more complex and sophisticated so that they require the intensive use of computers, both for running experiments as well as acquiring and processing the resulting data. This title explores new experimental and computational methods and covers various topics such as: Computer-aided Models; Image Analysis Applications; Noise Filtration of Shockwave Propagation; Finite Element Simulations.

Focused on efficient simulation-driven multi-fidelity optimization techniques, this monograph on simulation-driven optimization covers simulations utilizing physics-based low-fidelity models, often based on coarse-discretization simulations or other types of simplified physics representations, such as analytical models. The methods presented in the book exploit as much as possible any knowledge about the system or device of interest embedded in the low-fidelity model with the purpose of reducing the computational overhead of the design process. Most of the techniques described in the book are of response correction type and can be split into parametric (usually based on analytical formulas) and non-parametric, i.e., not based on analytical formulas. The latter, while more complex in implementation, tend to be more efficient. The book presents a general formulation of response correction techniques as well as a number of specific methods, including those based on correcting the low-fidelity model response (output space mapping, manifold mapping, adaptive response correction and shape-preserving response prediction), as well as on suitable modification of design specifications. Detailed formulations, application examples and the discussion of advantages and disadvantages of these techniques are also included. The book demonstrates the use of the discussed techniques for solving real-world engineering design problems, including applications in microwave engineering, antenna design, and aero/hydrodynamics.

The motion of a particle in a random potential in two or more dimensions is chaotic, and the trajectories in deterministically chaotic systems are effectively random. It is therefore no surprise that there are links between the quantum properties of disordered systems and those of simple chaotic systems. The question is, how deep do the connec tions go? And to what extent do the mathematical techniques designed to understand one problem lead to new insights into the other? The canonical problem in the theory of disordered mesoscopic systems is that of a particle moving in a random array of scatterers. The aim is to calculate the statistical properties of, for example, the quantum energy levels, wavefunctions, and conductance fluctuations by averaging over different arrays; that is, by averaging over an ensemble of different realizations of the random potential. In some regimes, corresponding to energy scales that are large compared to the mean level spacing, this can be done using diagrammatic perturbation theory. In others, where the discreteness of the quantum spectrum becomes important, such an approach fails. A more powerful method, devel oped by Efetov, involves representing correlation functions in terms of a supersymmetric nonlinear sigma-model. This applies over a wider range of energy scales, covering both the perturbative and non-perturbative regimes. It was proved using this method that energy level correlations in disordered systems coincide with those of random matrix theory when the dimensionless conductance tends to infinity."

Rigorous presentation of Mathematical Homogenization Theory is the subject of numerous publications. This book, however, is intended to fill the gap in the analytical and numerical performance of the corresponding asymptotic analysis of the static and dynamic behaviors of heterogenous systems. Numerous concrete applications to composite media, heterogeneous plates and shells are considered. A lot of details, numerical results for cell problem solutions, calculations of high-order terms of asymptotic expansions, boundary layer analysis etc., are included.

This book contains a sampling of papers presented at the June 2-5, 2002 International Workshop on Bifurcations andamp; Instabilities in Geomechanics (IWBI 2002). The scope of the Workshop includes analytical approaches, numerical methods, and experimental techniques.

This book is a collection of papers presented at the 'Forum "Math-for-Industry" 2016 ' (FMfl2016), held at Queensland University of Technology, Brisbane, Australia, on November 21-23, 2016. The theme for this unique and important event was "Agriculture as a Metaphor for Creativity in All Human Endeavors", and it brought together leading international mathematicians and active researchers from universities and industry to discuss current challenging topics and to promote interactive collaborations between mathematics and industry. The success of agricultural practice relies fundamentally on its interconnections with and dependence on biology and the environment. Both play essential roles, including the biological adaption to cope with environmental challenges of biotic and abiotic stress and global warming. The book highlights the development of mathematics within this framework that successful agricultural practice depends upon and exploits.

The articles in this book are derived from the Third International Conference of the same name, held June 29-July 3, 1998. Topics include: nonlinear exaltations in condensed systems, evolution of complex systems, dynamics and structure of molecular and biomolecular systems, mathematical models of transfer processes in nonlinear systems and numerical modeling and algorithms.

Contains a compact disc with nearly 200 microcomputer programs illustrating a wide range of reliability and statistical analyses Mechanical Reliability Improvement provides probability and statistical concepts developed using pseudorandom numbers enumeration-, simulation-, and randomization-based statistical analyses for comparison of the test performance of alternative designs, as well as simulation- and randomization-based tests for examination of the credibility of statistical presumptions and discusses centroid and moment of inertia analogies for mean and variance the organization structure of completely randomized, randomized complete block, and split spot experiment test programs

This work comprises the proceedings of a conference held last year in Rhodes, Greece, to assess developments during the last 20 years in the field of nonlinear dynamics in geosciences. The volume has its own authority as part of the Aegean Conferences cycle, but it also brings together the most up-to-date research from the atmospheric sciences, hydrology, geology, and other areas of geosciences, and discusses the advances made and the future directions of nonlinear dynamics.