Importance Sampling: Applications in Communications and Detection / Edition 1

by Rajan Srinivasan

Overview

This research monograph deals with fast shastic simulation based on importance sampling (IS) principles and some of its applications. It is in large part devoted to an adaptive form of IS that has proved to be effective in applications that involve the estimation of probabilities of rare events. Rare events are often encountered in scientific and engineering processes. Their charac­ terization is especially important as their occurrence can have catastrophic consequences of varying proportions. Examples range from fracture due to material fatigue in engineering structures to exceedance of dangerous levels during river water floods to false target declarations in radar systems. Fast simulation using IS is essentially a forced Monte Carlo procedure designed to hasten the occurrence of rare events. Development of this simu­ lation method of analysis of scientific phenomena is usually attributed to the mathematician von Neumann, and others. Since its inception, MC simulation has found a wide range of employment, from statistical thermodynamics in disordered systems to the analysis and design of engineering structures characterized by high complexity. Indeed, whenever an engineering problem is analytically intractable (which is often the case) and a solution by nu­ merical techniques prohibitively expensive computationally, a last resort to determine the input-output characteristics of, or states within, a system is to carry out a simulation.

Product Details

ISBN-13:	9783540434207
Publisher:	Springer Berlin Heidelberg
Publication date:	08/15/2002
Series:	Engineering Online Library
Edition description:	2002
Pages:	242
Product dimensions:	6.10(w) x 9.25(h) x 0.02(d)

Table of Contents

1. Elements of Importance Sampling.- 2. Methods of Importance Sampling.- 3. Sums of Random Variables.- 4. Detection Theory.- 5. CFAR detection.- 6. Ensemble CFAR detection.- 7. Blind Simulation.- 8. Digital Communications.- References.