This book deals with the numerical approximation of partial differential equations. Its scope is to provide a thorough illustration of numerical methods, carry out their stability and convergence analysis, derive error bounds, and discuss the algorithmic aspects relative to their implementation. A sound balancing of theoretical analysis, description of algorithms and discussion of applications is one of its main features. Many kinds of problems are addressed. A comprehensive theory of Galerkin method and its variants, as well as that of collocation methods, are developed for the spatial discretization. These theories are then specified to two numerical subspace realizations of remarkable interest: the finite element method and the spectral method. From the reviews: "...The book is excellent and is addressed to post-graduate students, research workers in applied sciences as well as to specialists in numerical mathematics solving PDE. Since it is written very clearly, it would be acceptable for undergraduate students in advanced courses of numerical mathematics. Readers will find this book to be a great pleasure."--MATHEMATICAL REVIEWS
CONTENT
Basic Concepts and Methods for PDEsโ{128}{153} Approximation -- Numerical Solution of Linear Systems -- Finite Element Approximation -- Polynomial Approximation -- Galerkin, Collocation and Other Methods -- Approximation of Boundary Value Problems -- Elliptic Problems: Approximation by Galerkin and Collocation Methods -- Elliptic Problems: Approximation by Mixed and Hybrid Methods -- Steady Advection-Diffusion Problems -- The Stokes Problem -- The Steady Navier-Stokes Problem -- Approximation of Initial-Boundary Value Problems -- Parabolic Problems -- Unsteady Advection-Diffusion Problems -- The Unsteady Navier-Stokes Problem -- Hyperbolic Problems
Mathematics
Mathematical analysis
Analysis (Mathematics)
Numerical analysis
Physics
Applied mathematics
Engineering mathematics
Mathematics
Analysis
Numerical Analysis
Appl.Mathematics/Computational Methods of Engineering
Theoretical Mathematical and Computational Physics
