The Computational Complexity of Differential and Integral Equations (Hardcover)

Hardcover. This book is concerned with a central question in numerical analysis: the approximate solution of differential or integral equations by algorithms using incomplete information. This situation often arises for equations of the form Lu = f, where f is some function defined on a domain and L is a differential operator. The function f may not be given exactly - we might only know its value at a finite number of points in the domain. Consequently the best that can behoped for is to solve the equation to within a given accuracy at minimal cost or complexity.The author develops the theory of the complexity of the solutions to differential andintegral equations and discusses the relationship between the worst-case setting and other (sometimes more tractable) related settings such as the average case, probabilistic, asymptotic, and randomized settings. Furthermore, he studies to what extent standard algorithms (such as finite element methods for elliptic problems) are optimal.This approach is discussed in depth in the context of two-point boundary value problems, linear elliptic partial differential equations,integral equations, ordinary differential equations, and ill-posed problems. As a result, this volume should appeal to mathematicians and numerical analysts working on the approximate solution ofdifferential and integral equations as well as to complexity theorists addressing related questions in this area. This book is concerned with a central question in numerical analysis: how efficient can algorithms be made given only incomplete information about a differential or integral equation? This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…