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Julius S. Bendat

Random Data

Analysis and Measurement Procedures

€ 210.95

A timely update of the classic book on the theory and application of random data analysisFirst published in 1971, Random Data served as an authoritative book on the analysis

Taal / Language : English


Preface to the Third Edition.

Glossary of Symbols.

1. Basic Descriptions and Properties.

1.1. Deterministic Versus Random Data.

1.2. Classifications of Deterministic Data.

1.3. Classifications of Random Data.

1.4. Analysis of Random Data.

2. Linear Physical Systems.

2.1. Constant Parameter Linear Systems.

2.2. Basic Dynamic Characteristics.

2.3. Frequency Response Functions.

2.4. Illustrations of Frequency Response Functions.

2.5. Practical Considerations.

3. Probability Fundamentals.

3.1. One Random Variable.

3.2. Two Random Variables.

3.3. Gaussian (Normal) Distribution.

3.4. Rayleigh Distribution.

3.5. Higher Order Changes of Variables.

4. Statistical Principles.

4.1. Sample Values and Parameter Estimation.

4.2. Important Probability Distribution Functions.

4.3. Sampling Distributions and Illustrations.

4.4. Confidence Intervals.

4.5. Hypothesis Tests.

4.6. Correlation and Regression Procedures.

5. Stationary Random Processes.

5.1. Basic Concepts.

5.2. Spectral Density Functions.

5.3. Ergodic and Gaussian Random Processes.

5.4. Derivative Random Processes.

5.5. Level Crossings and Peak Values.

6. Single Input/Output Relationships.

6.1. Single Input/Single Output Models.

6.2. Single Input/Multiple Output Models.

7. Multiple Input/Output Relationships.

7.1. Multiple Input/Single Output Models.

7.2. Two Input/One Output Models.

7.3. General and Conditioned Multiple Input Models.

7.4. Modified Procedure to Solve Multiple Input/Single Output Models.

7.5. Matrix Formulas for Multiple Input/Multiple Output Models.

8. Statistical Errors in Basic Estimates.

8.1. Definition of Errors.

8.2. Mean and Mean Square Value Estimates.

8.3. Probability Density Function Estimates.

8.4. Correlation Function Estimates.

8.5. Autospectral Density Function Estimates.

8.6. Record Length Requirements.

9. Statistical Errors in Advanced Estimates.

9.1. Cross Spectral Density Function Estimates.

9.2. Single Input/Output Model Estimates.

9.3. Multiple Input/Output Model Estimates.

10. Data Acquisition and Processing.

10.1. Data Acquisition.

10.2. Data Conversion.

10.3. Data Qualification.

10.4. Data Analysis Procedures.

11. Data Analysis.

11.1. Data Preparation.

11.2. Fourier Series and Fast Fourier Transforms.

11.3. Probability Density Functions.

11.4. Autocorrelation Functions.

11.5. Autospectral Density Functions.

11.6. Joint Record Functions.

11.7. Multiple Input/Output Functions.

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.

13. The Hilbert Transform.

13.1. Hilbert Transforms for General Records.

13.2. Hilbert Transforms for Correlation Functions.

13.3. Envelope Detection Followed by Correlation.

14. Nonlinear System Analysis.

14.1. Zero Memory and Finite Memory Nonlinear Systems.

14.2. Square Law and 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.


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.

Extra informatie: 
640 pagina's
Januari 2010
998 gram
235 x 159 x 32 mm
Wiley-Blackwell us

Levertijd: 5 tot 11 werkdagen