Book description
A timely update of the classic book on the theory and application of random data analysis
First published in 1971, Random Data served as an authoritative book on the analysis of experimental physical data for engineering and scientific applications. This Fourth Edition features coverage of new developments in random data management and analysis procedures that are applicable to a broad range of applied fields, from the aerospace and automotive industries to oceanographic and biomedical research.
This new edition continues to maintain a balance of classic theory and novel techniques. The authors expand on the treatment of random data analysis theory, including derivations of key relationships in probability and random process theory. The book remains unique in its practical treatment of nonstationary data analysis and nonlinear system analysis, presenting the latest techniques on modern data acquisition, storage, conversion, and qualification of random data prior to its digital analysis. The Fourth Edition also includes:
A new chapter on frequency domain techniques to model and identify nonlinear systems from measured input/output random data
New material on the analysis of multipleinput/singleoutput linear models
The latest recommended methods for data acquisition and processing of random data
Important mathematical formulas to design experiments and evaluate results of random data analysis and measurement procedures
Answers to the problem in each chapter
Comprehensive and selfcontained, Random Data, Fourth Edition is an indispensible book for courses on random data analysis theory and applications at the upperundergraduate and graduate level. It is also an insightful reference for engineers and scientists who use statistical methods to investigate and solve problems with dynamic data.
Table of contents
 Cover
 Series Page 1
 Series Page 2
 Title Page
 Copyright
 Dedication
 Preface
 Preface to the Third Edition
 Glossary of Symbols
 CHAPTER 1: Basic Descriptions and Properties
 CHAPTER 2: Linear Physical Systems
 CHAPTER 3: Probability Fundamentals
 CHAPTER 4: Statistical Principles
 CHAPTER 5: Stationary Random Processes
 CHAPTER 6: SingleInput/Output Relationships
 CHAPTER 7: MultipleInput/Output Relationships
 CHAPTER 8: Statistical Errors in Basic Estimates
 CHAPTER 9: Statistical Errors in Advanced Estimates
 CHAPTER 10: Data Acquisition and Processing
 CHAPTER 11: Data Analysis

CHAPTER 12: Nonstationary Data Analysis
 12.1 CLASSES OF NONSTATIONARY DATA
 12.2 PROBABILITY STRUCTURE OF NONSTATIONARY DATA
 12.3 NONSTATIONARY MEAN VALUES
 12.4 NONSTATIONARY MEAN SQUARE VALUES
 12.5 CORRELATION STRUCTURE OF NONSTATIONARY DATA
 12.6 SPECTRAL STRUCTURE OF NONSTATIONARY DATA
 12.7 INPUT/OUTPUT RELATIONS FOR NONSTATIONARY DATA
 PROBLEMS
 REFERENCES
 CHAPTER 13: The Hilbert Transform

CHAPTER 14: Nonlinear System Analysis
 14.1 ZEROMEMORY AND FINITEMEMORY NONLINEAR SYSTEMS
 14.2 SQUARELAWAND CUBIC NONLINEAR MODELS
 14.3 VOLTERRA NONLINEAR MODELS
 14.4 SI/SO MODELS WITH PARALLEL LINEAR AND NONLINEAR SYSTEMS
 14.5 SI/SO MODELS WITH NONLINEAR FEEDBACK
 14.6 RECOMMENDED NONLINEAR MODELS AND TECHNIQUES
 14.7 DUFFING SDOF NONLINEAR SYSTEM
 14.8 NONLINEAR DRIFT FORCE MODEL
 PROBLEMS
 REFERENCES
 Bibliography
 Appendix A: Statistical Tables
 Appendix B: Definitions for Random Data Analysis
 List of Figures
 List of Tables
 List of Examples
 Answers to Problems in Random Data
 Index
Product information
 Title: Random Data: Analysis and Measurement Procedures, Fourth Edition
 Author(s):
 Release date: February 2010
 Publisher(s): Wiley
 ISBN: 9780470248775
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