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 multiple-input/single-output 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 self-contained, Random Data, Fourth Edition is an indispensible book for courses on random data analysis theory and applications at the upper-undergraduate 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: Single-Input/Output Relationships
- CHAPTER 7: Multiple-Input/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 ZERO-MEMORY AND FINITE-MEMORY NONLINEAR SYSTEMS
- 14.2 SQUARE-LAWAND 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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