The finite element method is one of the major tools used in the numerical solution of partial differential equations in science and engineering. This book offers a fundamental and practical introducti
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 co
This book aims to present meshfree methods in a friendly and straightforward manner, so that beginners can very easily understand, comprehend, program, implement, apply and extend these methods. It p
An elementary first course for students in mathematics and engineeringPractical in approach: examples of code are provided for students to debug, and tasks – with full solutions – are provided at the
This book's coverage of differential equations begins with the structure of the solution space and the stability and periodic properties of linear ordinary and Volterra differential equations. Discuss
This is the 2005 second edition of a highly successful and well-respected textbook on the numerical techniques used to solve partial differential equations arising from mathematical models in science, engineering and other fields. The authors maintain an emphasis on finite difference methods for simple but representative examples of parabolic, hyperbolic and elliptic equations from the first edition. However this is augmented by new sections on finite volume methods, modified equation analysis, symplectic integration schemes, convection-diffusion problems, multigrid, and conjugate gradient methods; and several sections, including that on the energy method of analysis, have been extensively rewritten to reflect modern developments. Already an excellent choice for students and teachers in mathematics, engineering and computer science departments, the revised text includes more latest theoretical and industrial developments.
Assuming only an elementary background in discrete mathematics, this textbook is an excellent introduction to the probabilistic techniques and paradigms used in the development of probabilistic algori
This text combines technical and engineering mathematical concepts at a basic level using MATLABr for support and analysis. Once math concepts are introduced and understood using conventional techniq
This book offers a comprehensive presentation of some of the most successful and popular domain decomposition preconditioners for finite and spectral element approximations of partial differential equ
Despite the continued rapid advance in computing speed and memory the increase in the complexity of models used by engineers persists in outpacing them. Even where there is access to the latest hardwa
Hageman, with a large electric company, and Young (numerical analysis, U. of Texas-Austin) explain how to use iterative methods to solve large, sparse systems of linear algebraic equations. They focus
A gentle introduction to advanced topics such as parallel computing, multigrid methods, and special methods for systems of PDEs. The goal of all chapters is to ‘compute’ solutions to problems, hence a
This is a textbook in numerical analysis and scientific computing intended for students with a year of calculus coursework, and familiarity with matrix algebra and differential equations. Leader prefe
After an introduction to the subject area and a concise treatment of the technical foundations for the subsequent chapters, this book features 14 chapters on state-of-the-art graph drawing software sy
