الصفحة 1
الصفحة 1
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Open Quantum Systems II : The Markovian Approach

These books present in a self-contained way the mathematical theories involved in the modeling of such phenomena. They describe physically relevant models, develop their mathematical analysis and derive their physical implications. Volume II is dedicated to the Markovian formalism of classical and quantum open systems. A complete exposition of noise theory, Markov processes and stochastic differential equations, both in the classical and the quantum context, is provided. These mathematical tools are put into perspective with physical motivations and applications.

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Open Quantum Systems I : The Hamiltonian Approach

These books present in a self-contained way the mathematical theories involved in the modeling of such phenomena. They describe physically relevant models, develop their mathematical analysis and derive their physical implications. This Volume, I the Hamiltonian description of quantum open systems is discussed. This includes an introduction to quantum statistical mechanics and its operator algebraic formulation, modular theory, spectral analysis and their applications to quantum dynamical systems.

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Online Storage Systems and Transportation Problems with Applications : Optimization Models and Mathematical Solutions

This books covers the analysis and development of online algorithms involving exact optimization and heuristic techniques, and their application to solve two real life problems. The first problem is concerned with a complex technical system: a special carousel based high-speed storage system - Rotastore. It is shown that this logistic problem leads to an NP-hard Batch PreSorting problem which is not easy to solve optimally in offline situations. The second problem originates in the health sector and leads to a vehicle routing problem. Reasonable solutions for the offline case covering a whole day with a few hundred orders are constructed with a heuristic approach, as well as by simulated annealing. Optimal solutions for typical online instances are computed by an efficient column enumeration approach leading to a set partitioning problem and a set of routing-scheduling subproblems. The latter are solved exactly with a branch-and-bound method which prunes nodes if they are value-dominated by previous found solutions or if they are infeasible with respect to the capacity or temporal constraints.

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On Communication : An interdisciplinary and mathematical approach

This book offers a radical new approach for the understanding of communication. By using the theoretical framework of complex systems theory communication is defined as the interplay of social and cognitive dynamics: communicators are modelled as complex cognitive systems who interact according to social rules and generate communicative systems. Messages generate meaning, which is understood as an attractor in the cognitive system of the receiver. Information is measured via the difference between a factual message and the message expected by the receiver.

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OMDoc : An Open Markup Format for Mathematical Documents [version 1.2]

Computers arechanging the way wethink. Of course,nearly all desk-workers have access to computers and use them to email their colleagues, search the Web for information and prepare documents. But I’m not referring to that. I mean that people have begun to think about what they do in compu- tional terms and to exploit the power of computers to do things that would previously have been unimaginable. This observation is especially true of mathematicians.

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Official Statistics 4.0 : Verified Facts for People in the 21st Century

Explores official statistics and their social function in modern societies. Digitisation and globalisation are creating completely new opportunities and risks, a context in which facts (can) play an enormously important part if they are produced with a quality that makes them credible and purpose-specific. In order for this to actually happen, official statistics must continue to actively pursue the modernisation of their working methods.

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Objective information theory

Objective Information Theory (OIT) is proposed to represent and compute the information in a large-scale complex information system with big data in this monograph. To formally analyze, design, develop, and evaluate the information, OIT interprets the information from essential nature, measures the information from mathematical properties, and models the information from concept, logic, and physic. As the exemplified applications, Air Traffic Control System (ATCS) and Smart Court SoSs (System of Systems) are introduced for practical OITs.

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Numerical Techniques for Chemical and Biological Engineers Using MATLAB® : A Simple Bifurcation Approach

This book addresses the bifurcation characteristics of chemical and biological processes as the general case and treats systems with a unique steady state as special cases. It uses a system approach which is the most efficient for knowledge organization and transfer. The book develops mathematical models for many commercial processes utilizing the mass-, momentum-, and heat-balance equations coupled to the rates of the processes that take place within the boundaries of the system. The models are solved numerically through MATLAB codes with emphasis on the design and optimization of the chemical and biological industrial equipment and plants.

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Numerical Solution of Partial Differential Equations on Parallel Computers

The scientific fields of Ma- ematics and Physics provide a powerful vehicle for such descriptions in terms of Partial Differential Equations (PDEs). Formulated as such equations, physical laws can become subject to computational and analytical studies. In the computational setting, the equations can be discreti ed for ef?cient solution on a computer, leading to valuable tools for simulation of natural and man-made processes. Numerical so- tion of PDE-based mathematical models has been an important research topic over centuries, and will remain so for centuries to come. In the context of computer-based simulations, the quality of the computed results is directly connected to the model’s complexity and the number of data points used for the computations. Therefore, computational scientists tend to ?ll even the largest and most powerful computers they can get access to, either by increasing the si e of the data sets, or by introducing new model terms that make the simulations more realistic, or a combination of both. Today, many important simulation problems can not be solved by one single computer, but calls for parallel computing.

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Numerical Methods Using Java : For Data Science, Analysis, and Engineering

Covers a wide range of topics, including chapters on linear algebra, root finding, curve fitting, differentiation and integration, solving differential equations, random numbers and simulation, a whole suite of unconstrained and constrained optimization algorithms, statistics, regression and time series analysis. The mathematical concepts behind the algorithms are clearly explained, with plenty of code examples and illustrations to help even beginners get started. You will: Program in Java using a high-performance numerical library / Learn the mathematics for a wide range of numerical computing algorithms / Convert ideas and equations into code / Put together algorithms/ and classes to build your own engineering solution / Build solvers for industrial optimization problems / Do data analysis using basic and advanced statistics

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Numerical Methods in Finance

The use of mathematical models and numerical techniques in finance is a growing practice, and an increasing number of applied mathematicians are working on applications in finance and business. This book presents some exciting developments arising from the combination of mathematics, numerical analysis, and finance. It covers a wide range of topics, from portfolio management and asset pricing, to performance, risk, debt and real option evaluation. It also presents applications of a variety of cutting edge approaches and techniques, including robust control, min-max optimisation, Bessel processes, stochastic viability, variational inequalities, and Monte-Carlo test techniques. The book also presents surveys of models and approaches in specific areas in finance, such as corporate debt valuation and portfolio selection

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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 General and Structured Eigenvalue Problems

The purpose of this book is to describe recent developments in solving eig- value problems, in particular with respect to the QR and QZ algorithms as well as structured matrices. Outline Mathematically speaking, the eigenvalues of a square matrix A are the roots of its characteristic polynomial det(A??I). An invariant subspace is a linear subspace that stays invariant under the action of A. In realistic applications, it usually takes a long process of simpli?cations, linearizations and discreti- tions before one comes up with the problem of computing the eigenvalues of a matrix. In some cases, the eigenvalues have an intrinsic meaning, e.g., for the expected long-time behavior of a dynamical system; in others they are just meaningless intermediate values of a computational method. The same applies to invariant subspaces, which for example can describe sets of initial states for which a dynamical system produces exponentially decaying states. Computing eigenvalues has a long history, dating back to at least 1846 when Jacobi [172] wrote his famous paper on solving symmetric eigenvalue problems. Detailed historical accounts of this subject can be found in two papers by Golub and van der Vorst [140, 327].

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Numerical Mathematics and Advanced Applications ENUMATH 2019 ; European Conference, Egmond aan Zee, The Netherlands, September 30 - October 4

It contians basic aspects and new trends in numerical mathematics and scientific and industrial applications, all examined at the highest level of international expertise.

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Numerical Mathematics and Advanced Applications ; Proceedings of ENUMATH 2005 the 6th European Conference on Numerical Mathematics and Advanced Applications, Santiago de Compostela, Spain, July 2005

This book include applications such as atmosphere and ocean, water pollution, electromagnetism, interface problems, waves, finance, heat transfer, unbounded domains, numerical linear algebra, convection-diffusion, fluid-structure, plates, solids, hyperbolic equations, multiphase flow, Navier-Stokes, singular perturbation problems, non linear PDE, control, parabolic equations, as well as methodologies such as a posteriori error estimates, discontinuous Galerkin methods, multiscale methods, optimization, adaptive methods, domain decomposition techniques, exponential integrators, hp-finite elements, level set methods, fractional step methods, penalty procedures, and finite volumes. The book gives an extensive overview of the most recent research in scientific computing, providing to the reader the latest developments concerning the mathematical issues and the applications of this active field of science.

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Numerical computation, data analysis and software in mathematics and engineering

Include the aspects of the meshless method, numerical simulation, mathematical models, deep learning and data analysis. Meshless methods, such as the improved element-free Galerkin method, the dimension-splitting, interpolating, moving, least-squares method, the dimension-splitting, generalized, interpolating, element-free Galerkin method and the improved interpolating, complex variable, element-free Galerkin method, are presented. Some complicated problems, such as tge cold roll-forming process, ceramsite compound insulation block, crack propagation and heavy-haul railway tunnel with defects, are numerically analyzed.

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Nonsmooth Vector Functions and Continuous Optimization

A recent significant innovation in mathematical sciences has been the progressive use of nonsmooth calculus, an extension of the differential calculus, as a key tool of modern analysis in many areas of mathematics, operations research, and engineering. Focusing on the study of nonsmooth vector functions, this book presents a comprehensive account of the calculus of generalized Jacobian matrices and their applications to continuous nonsmooth optimization problems and variational inequalities in finite dimensions.

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Nonsmooth Mechanics and Analysis : Theoretical and Numerical Advances

Nonsmooth mechanics concerns mechanical situations with possible nondifferentiable relationships, eventually discontinuous, as unilateral contact, dry friction, collisions, plasticity, damage, and phase transition. The basis of the approach consists in dealing with such problems without resorting to any regularization process. Indeed, the nonsmoothness is due to simplified mechanical modeling; a more sophisticated model would require too large a number of variables, and sometimes the mechanical information is not available via experimental investigations. Therefore, the mathematical formulation becomes nonsmooth; regularizing would only be a trick of arithmetic without any physical justification. Nonsmooth analysis was developed, especially in Montpellier, to provide specific theoretical and numerical tools to deal with nonsmoothness. It is important not only in mechanics but also in physics, robotics, and economics.

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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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Nonparametric Functional Data Analysis : Theory and Practice

Modern apparatuses allow us to collect samples of functional data, mainly curves but also images. On the other hand, nonparametric statistics produces useful tools for standard data exploration. This book links these two fields of modern statistics by explaining how functional data can be studied through parameter-free statistical ideas. This book starts from theoretical foundations including functional nonparametric modeling, description of the mathematical framework, construction of the statistical methods, and statements of their asymptotic behaviors. It proceeds to computational issues including R and S-PLUS routines. Several functional datasets in chemometrics, econometrics, and pattern recognition are used to emphasize the wide scope of nonparametric functional data analysis in applied sciences. The companion Web site includes R and S-PLUS routines, command lines for reproducing examples presented in the book, and the functional datasets. Rather than set application against theory, this book is really an interface of these two features of statistics. A special effort has been made in writing this book to accommodate several levels of reading.

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