الصفحة 1
الصفحة 1
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Numerical methods in computational finance : A partial differential equation (PDE/FDM) approach

This book is a detailed and step-by-step introduction to the mathematical foundations of ordinary and partial differential equations, their approximation by the finite difference method and applications to computational finance.

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Numerical Methods for Controlled Stochastic Delay Systems

The Markov chain approximation methods are widely used for the numerical solution of nonlinear stochastic control problems in continuous time. This book extends the methods to stochastic systems with delays. Because such problems are infinite-dimensional, many new issues arise in getting good numerical approximations and in the convergence proofs. Useful forms of numerical algorithms and system approximations are developed in this work, and the convergence proofs are given. All of the usual cost functions are treated as well as singular and impulsive controls. A major concern is on representations and approximations that use minimal memory.

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Numerical Mathematics

Numerical mathematics is the branch of mathematics that proposes, develops, analyzes and applies methods from scientific computing to several fields including analysis, linear algebra, geometry, approximation theory, functional equations, optimization and differential equations. Other disciplines, such as physics, the natural and biological sciences, engineering, and economics and the financial sciences frequently give rise to problems that need scientific computing for their solutions. As such, numerical mathematics is the crossroad of several disciplines of great relevance in modern applied sciences, and can become a crucial tool for their qualitative and quantitative analysis.

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Numerical Approximation Methods for Elliptic Boundary Value Problems : Finite and Boundary Elements

Although the aim of this book is to give a unified introduction into finite and boundary element methods, the main focus is on the numerical analysis of boundary integral and boundary element methods. Starting from the variational formulation of elliptic boundary value problems boundary integral operators and associated boundary integral equations are introduced and analyzed. By using finite and boundary elements corresponding numerical approximation schemes are considered.

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Numerical Analysis and Its Applications ; 3rd International Conference, NAA 2004, Rousse, Bulgaria, June 29 - July 3, 2004, Revised Selected Papers

Constitutes the refereed post-proceedings of the Third International Conference on Numerical Analysis and Its Applications, held in Bulgaria in June/July 2004. This book addresses various aspects of numerical analysis. It covers the application fields such as computational sciences and engineering, chemistry, physics, economics, and simulation.

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Numerical analysis

Introduces readers to the theory and application of modern numerical approximation techniques. Providing an accessible treatment that only requires a calculus prerequisite, the authors explain how, why, and when approximation techniques can be expected to work-and why, in some situations, they fail. A wealth of examples and exercises develop readers' intuition, and demonstrate the subject's practical applications to important everyday problems in math, computing, engineering, and physical science disciplines.

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Nonparametric Monte Carlo Tests and Their Applications

A fundamental issue in statistical analysis is testing the fit of a particular probability model to a set of observed data. Monte Carlo approximation to the null distribution of the test provides a convenient and powerful means of testing model fit. Nonparametric Monte Carlo Tests and Their Applications proposes a new Monte Carlo-based methodology to construct this type of approximation Every chapter of the book includes algorithms, simulations, and theoretical deductions. The prerequisites for a full appreciation of the book are a modest knowledge of mathematical statistics and limit theorems in probability,empirical process theory.

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Nonlinear Analyses and Algorithms for Speech Processing ; International Conference on Non-Linear Speech Processing, NOLISP 2005, Barcelona, Spain, April 19-22, 2005, Revised Selected Papers

We present in this volume the collection of ?nally accepted papers of NOLISP 2005 conference. It has been the third event in a series of events related to N- linear speech processing, in the framework of the European COST action 277 “Nonlinear speech processing”. Many speci?cs of the speech signal are not well addressed by conv- tional models currently used in the ?eld of speech processing. The purpose of NOLISP is to present and discuss novel ideas, work and results related to alternative techniques for speech processing, which depart from mainstream approaches. With this intention in mind, we provide an open forum for discussion. Alt- nate approaches are appreciated, although the results achieved at present may not clearly surpass results based on state-of-the-art methods. The call for papers was launched at the beginning of 2005, addressing the following domains: 1. Non-Linear Approximation and Estimation 2. Non-Linear Oscillators and Predictors 3. Higher-Order Statistics 4. Independent Component Analysis 5. Nearest Neighbors 6. Neural Networks 7. Decision Trees 8. Non-Parametric Models 9. Dynamics of Non-Linear Systems 10. Fractal Methods 11. Chaos Modeling 12. Non-Linear Di?erential Equations 13. Others All the main ?elds of speech processing are targeted by the workshop, namely: 1. Speech Coding:Thebit rateavailablefor speechsignalsmustbe strictly l- ited in order to accommodate the constraints of the channel resource.

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Nexus Network Journal 9,1 : Architecture and Mathematics

This issue is dedicated to various kinds of patterns in architecture. Buthayna Eilouti and Amer Al-Jokhadar address patterns in shape grammars in the ground plans of Mamluk madrasas, religious schools. Giulio Magli goes back further in history, to the age of Greek colonies in Italy before they were conquered by the Romans, to examine patterns in urban design. In Traditional Patterns in Pyrgi of Chios: Mathematics and Community Charoula Stathopoulou examines the geometric patterns that decorate the buildings of the town of Pyrgi, on the Greek island of Chios. Curve Fitting is a study of ways to construct a function so that its graph most closely approximates the pattern given by a set of points.

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Neural Networks : Computational Models and Applications

Neural Networks: Computational Models and Applications covers a wealth of important theoretical and practical issues in neural networks, including the learning algorithms of feed-forward neural networks, various dynamical properties of recurrent neural networks, winner-take-all networks and their applications in broad manifolds of computational intelligence: pattern recognition, uniform approximation, constrained optimization, NP-hard problems, and image segmentation. By presenting various computational models, this book is developed to provide readers with a quick but insightful understanding of the broad and rapidly growing areas in the neural networks domain. Besides laying down fundamentals on artificial neural networks, this book also studies biologically inspired neural networks. Some typical computational models are discussed, and subsequently applied to objection recognition, scene analysis and associative memory. The studies of bio-inspired models have important implications in computer vision and robotic navigation, as well as new efficient algorithms for image analysis.

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Monte Carlo Methods in Fuzzy Optimization

This book is a concise and readable introduction to Monte Carlo methods to find good approximate solutions to fuzzy optimization problems. Various basic applications and illustrative examples are presented in an understandable way. The aim of the book is to convince the reader that Monte Carlo methods can be useful in generating approximate solutions to fuzzy optimization problems.

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Mono-Cycle Photonics and Optical Scanning Tunneling Microscopy : Route to Femtosecond Ångstrom Technology

"Mono-Cycle Photonics and Optical Scanning Tunneling Microscopy" deals with both the ultrashort laser-pulse technology in the few- to mono-cycle region and the laser-surface-controlled scanning-tunneling microscopy (STM) extending into the spatiotemporal extreme technology. The former covers the theory of nonlinear pulse propagation beyond the slowly-varing-envelope approximation, the generation and active chirp compensation of ultrabroadband optical pulses, the amplitude and phase characterization of few- to mono-cycle pulses, and the feedback field control for the mono-cycle-like pulse generation. In addition, the wavelength-multiplex shaping of ultrabroadband pulse is described. The latter covers the CW-laser-excitation STM, the femtosecond-time-resolved STM and atomic-level surface phenomena controlled by femtosecond pulses.

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Molecular autoimmunity

The autoimmune disease paroxysmal cold hemoglobinuria, a rare hemolytic disorder. After a century of research, the list of autoimmune diseases has become impressive. With a prevalence of approximately 5% of the world-wide population, these chronic, debilitating conditions affect almost every major organ of the body and, for reasons that remain unclear, are much more prevalent in woman than in men. Despite our rapidly expanding knowledge of the cellular and molecular pathways that govern a normal immune response, deciphering the precise etiology of autoimmune diseases remains an important challenge. Over the last few years, our understanding of the pathogenesis of autoimmune diseases has improved rapidly, leading to the emergence of elegant immunointervention strategies. Molecular Autoimmunity illustrates how cutting-edge research is continuing to advance our understanding of autoimmune disease mechanisms and identifies novel therapeutic targets that provide a hope for effective future treatments. This volume contains a selected number of exciting advances in unraveling autoimmune reactions, and the resulting new armory of experimental immunotherapies that may lead to new ways of controlling autoimmune reactions.

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Modeling Uncertainty : An Examination of Stochastic Theory, Methods, and Applications

​Modeling Uncertainty: An Examination of Stochastic Theory, Methods, and Applications, is a volume undertaken by the friends and colleagues of Sid Yakowitz in his honor. Fifty internationally known scholars have collectively contributed 30 papers on modeling uncertainty to this volume. Each of these papers was carefully reviewed and in the majority of cases the original submission was revised before being accepted for publication in the book. The papers cover a great variety of topics in probability, statistics, economics, stochastic optimization, control theory, regression analysis, simulation, stochastic programming, Markov decision process, application in the HIV context, and others. There are papers with a theoretical emphasis and others that focus on applications. A number of papers survey the work in a particular area and in a few papers the authors present their personal view of a topic. It is a book with a considerable number of expository articles, which are accessible to a nonexpert - a graduate student in mathematics, statistics, engineering, and economics departments, or just anyone with some mathematical background who is interested in a preliminary exposition of a particular topic. Many of the papers present the state of the art of a specific area or represent original contributions which advance the present state of knowledge. In sum.

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Model Based Inference in the Life Sciences : A Primer on Evidence

The abstract concept of "information" can be quantified and this has led to many important advances in the analysis of data in the empirical sciences. This text focuses on a science philosophy based on "multiple working hypotheses" and statistical models to represent them. The fundamental science question relates to the empirical evidence for hypotheses in this set—a formal strength of evidence. Kullback-Leibler information is the information lost when a model is used to approximate full reality. Hirotugu Akaike found a link between K-L information (a cornerstone of information theory) and the maximized log-likelihood (a cornerstone of mathematical statistics). This combination has become the basis for a new paradigm in model based inference. The text advocates formal inference from all the hypotheses/models in the a priori set—multimodel inference.

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Mixed Finite Elements, Compatibility Conditions, and Applications : Lectures given at the C.I.M.E. Summer School held in Cetraro, Italy June 26–July 1, 2006

Since the early 70's, mixed finite elements have been the object of a wide and deep study by the mathematical and engineering communities. The fundamental role of this method for many application fields has been worldwide recognized and its use has been introduced in several commercial codes. An important feature of mixed finite elements is the interplay between theory and application. Discretization spaces for mixed schemes require suitable compatibilities, so that simple minded approximations generally do not work and the design of appropriate stabilizations gives rise to challenging mathematical problems.

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Mineral Deposit Research : Meeting the Global Challenge ; Proceedings of the Eighth Biennial SGA Meeting, Beijing, China, 18 - 21 August 2005

Represents a comprehensive summary of the developments across a range of subject matters that are relevant to the global research, mining and exploration community. This proceedings volume (including CD-ROM) is a compilation of approximately 400 extended abstracts (up to 4 pages long) of presentations given at the 8th Biennial SGA Meeting.

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Méthodes Numériques : Algorithmes, analyse et applications = Numerical Methods : Algorithms, Analysis and Applications

This book aims to present the theoretical and methodological foundations of numerical analysis. Particular attention is paid to the concepts of stability, precision and complexity of algorithms. Modern methods relating to the following topics are presented and analyzed in detail: solving linear and nonlinear systems, polynomial approximation, optimization, numerical integration, orthogonal polynomials, rapid transformations, ordinary differential equations. The techniques presented are illustrated by numerous tables and figures. Many examples and counter-examples are offered to allow the reader to develop his critical sense.

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Metamorphoses of Hamiltonian Systems with Symmetries

Modern notions and important tools of classical mechanics are used in the study of concrete examples that model physically significant molecular and atomic systems. The parametric nature of these examples leads naturally to the study of the major qualitative changes of such systems (metamorphoses) as the parameters are varied. The symmetries of these systems, discrete or continuous, exact or approximate, are used to simplify the problem through a number of mathematical tools and techniques like normalization and reduction. The book moves gradually from finding relative equilibria using symmetry, to the Hamiltonian Hopf bifurcation and its relation to monodromy and, finally, to generalizations of monodromy.

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Metaheuristic Procedures for Training Neural Networks

Metaheuristic Procedures For Training Neural Networks provides successful implementations of metaheuristic methods for neural network training. Apart from Chapter 1, which reviews classical training methods, the chapters are divided into three main categories. The first one is devoted to local search based methods, including Simulated Annealing, Tabu Search, and Variable Neighborhood Search.

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