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Mathematical Modelling
  • Language: en
  • Pages: 174

Mathematical Modelling

This volume is a collection of chapters that present key ideas and theories, as well as their rigorous applications, required for the development of mathematical models in areas such as travelling waves, epidemiology, the chemotaxis system, atrial fibrillation, and vortex nerve complexes. The techniques, methodologies and approaches adopted in this book have relevance in several other fields including physics, biology, and sociology. Each chapter should also assist readers in comfortably comprehending the related and underlying ideas. The companion volume (Contemporary Mathematics, Volume 786) is devoted to principle and theory.

Taylor Approximations for Stochastic Partial Differential Equations
  • Language: en
  • Pages: 224

Taylor Approximations for Stochastic Partial Differential Equations

  • Type: Book
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  • Published: 2011-12-08
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  • Publisher: SIAM

This book presents a systematic theory of Taylor expansions of evolutionary-type stochastic partial differential equations (SPDEs). The authors show how Taylor expansions can be used to derive higher order numerical methods for SPDEs, with a focus on pathwise and strong convergence. In the case of multiplicative noise, the driving noise process is assumed to be a cylindrical Wiener process, while in the case of additive noise the SPDE is assumed to be driven by an arbitrary stochastic process with H?lder continuous sample paths. Recent developments on numerical methods for random and stochastic ordinary differential equations are also included since these are relevant for solving spatially discretised SPDEs as well as of interest in their own right. The authors include the proof of an existence and uniqueness theorem under general assumptions on the coefficients as well as regularity estimates in an appendix.

Numerical Approximations of Stochastic Differential Equations with Non-Globally Lipschitz Continuous Coefficients
  • Language: en
  • Pages: 112

Numerical Approximations of Stochastic Differential Equations with Non-Globally Lipschitz Continuous Coefficients

Many stochastic differential equations (SDEs) in the literature have a superlinearly growing nonlinearity in their drift or diffusion coefficient. Unfortunately, moments of the computationally efficient Euler-Maruyama approximation method diverge for these SDEs in finite time. This article develops a general theory based on rare events for studying integrability properties such as moment bounds for discrete-time stochastic processes. Using this approach, the authors establish moment bounds for fully and partially drift-implicit Euler methods and for a class of new explicit approximation methods which require only a few more arithmetical operations than the Euler-Maruyama method. These moment bounds are then used to prove strong convergence of the proposed schemes. Finally, the authors illustrate their results for several SDEs from finance, physics, biology and chemistry.

Taylor Approximations for Stochastic Partial Differential Equations
  • Language: en
  • Pages: 234

Taylor Approximations for Stochastic Partial Differential Equations

  • Type: Book
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  • Published: 2011-01-01
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  • Publisher: SIAM

This book presents a systematic theory of Taylor expansions of evolutionary-type stochastic partial differential equations (SPDEs). The authors show how Taylor expansions can be used to derive higher order numerical methods for SPDEs, with a focus on pathwise and strong convergence. In the case of multiplicative noise, the driving noise process is assumed to be a cylindrical Wiener process, while in the case of additive noise the SPDE is assumed to be driven by an arbitrary stochastic process with Hl̲der continuous sample paths. Recent developments on numerical methods for random and stochastic ordinary differential equations are also included since these are relevant for solving spatially discretised SPDEs as well as of interest in their own right. The authors include the proof of an existence and uniqueness theorem under general assumptions on the coefficients as well as regularity estimates in an appendix.

Inverse Scattering Theory and Transmission Eigenvalues
  • Language: en
  • Pages: 259

Inverse Scattering Theory and Transmission Eigenvalues

  • Type: Book
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  • Published: 2022-12-07
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  • Publisher: SIAM

Inverse scattering theory is a major theme in applied mathematics, with applications to such diverse areas as medical imaging, geophysical exploration, and nondestructive testing. The inverse scattering problem is both nonlinear and ill-posed, thus presenting challenges in the development of efficient inversion algorithms. A further complication is that anisotropic materials cannot be uniquely determined from given scattering data. In the first edition of Inverse Scattering Theory and Transmission Eigenvalues, the authors discussed methods for determining the support of inhomogeneous media from measured far field data and the role of transmission eigenvalue problems in the mathematical devel...

Stochastic Partial Differential Equations and Related Fields
  • Language: en
  • Pages: 565

Stochastic Partial Differential Equations and Related Fields

  • Type: Book
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  • Published: 2018-07-03
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  • Publisher: Springer

This Festschrift contains five research surveys and thirty-four shorter contributions by participants of the conference ''Stochastic Partial Differential Equations and Related Fields'' hosted by the Faculty of Mathematics at Bielefeld University, October 10–14, 2016. The conference, attended by more than 140 participants, including PostDocs and PhD students, was held both to honor Michael Röckner's contributions to the field on the occasion of his 60th birthday and to bring together leading scientists and young researchers to present the current state of the art and promising future developments. Each article introduces a well-described field related to Stochastic Partial Differential Equ...

Analyticity Results in Bernoulli Percolation
  • Language: en
  • Pages: 114

Analyticity Results in Bernoulli Percolation

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Recent Developments in Computational Finance
  • Language: en
  • Pages: 481

Recent Developments in Computational Finance

Computational finance is an interdisciplinary field which joins financial mathematics, stochastics, numerics and scientific computing. Its task is to estimate as accurately and efficiently as possible the risks that financial instruments generate. This volume consists of a series of cutting-edge surveys of recent developments in the field written by leading international experts. These make the subject accessible to a wide readership in academia and financial businesses. The book consists of 13 chapters divided into 3 parts: foundations, algorithms and applications. Besides surveys of existing results, the book contains many new previously unpublished results.

Stability of Line Solitons for the KP-II Equation in $\mathbb {R}^2$
  • Language: en
  • Pages: 110

Stability of Line Solitons for the KP-II Equation in $\mathbb {R}^2$

The author proves nonlinear stability of line soliton solutions of the KP-II equation with respect to transverse perturbations that are exponentially localized as . He finds that the amplitude of the line soliton converges to that of the line soliton at initial time whereas jumps of the local phase shift of the crest propagate in a finite speed toward . The local amplitude and the phase shift of the crest of the line solitons are described by a system of 1D wave equations with diffraction terms.