Applications of Random Process Excursion Analysis

This book addresses one of the key problems in signal processing, the problem of identifying statistical properties of excursions in a random process in order to simplify the theoretical analysis and make it suitable for engineering applications. Precise and approximate formulas are explained, which are relatively simple and can be used for engineering applications such as the design of devices which can overcome the high initial uncertainty of the self-training period. The information presented in the monograph can be used to implement adaptive signal processing devices capable of detecting or recognizing the wanted signals (with a priori unknown statistical properties) against the background noise. The applications presented can be used in a wide range of fields including medicine, radiolocation, telecommunications, surface quality control (flaw detection), image recognition, thermal noise analysis for the design of semiconductors, and calculation of excessive load in mechanics.

Introduces English-speaking students and researchers in to the results obtained in the former Soviet/ Russian academic institutions within last few decades.Supplies a range of applications suitable for all levels from undergraduate to professionalContains computer simulations

Preface

Introduction

Chapter 1 Probability characteristics of random process excursions

Chapter 2 Study of integral parameters of excursions

Chapter 3 Estimation of distribution densities of excursion durations for random stationary broadband signals

Chapter 4 Estimating certain informative parameters of random process excursions above a given level

Chapter 5 Using a family of correlation functions of a clipped random process to increase the accuracy of level crossing parameters estimation

Chapter 6 Estimates obtained through the study of certain less known parameters of excursions in differentiable random processes

Chapter 7 Design methodology of adaptable analyzers used to measure characteristics of excursions in stationary random processes