Part Ⅰ　Review Chapters
Chapter 1　Review of Probability
1.1　Chapter Highlights
1.2　Definition of Probability
1.3　Conditional Probability
1.4　Bayes Theorem
1.5　Independent Events
1.6　Random Variables
1.7　Conditional Distributions and Densities
1.8　Functions of One Random Variable
1.9　Moments of a Random Variable
1.10　 Distributions with Two Random Variables
1.11　 Multiple Random Variables
1.12　 Mean-Square Error (MSE) Estimation
1.13　 Bibliographical Notes
1.14　 Problems
Chapter 2　Stochastic Processes
2.1　Chapter Highlights
2.2　Stationary Processes
2.3　Cyclostationary Processes
2.4　Averages and Ergodicity
2.5　Autocorrelation Function
2.6　Power Spectral Density
2.7　Discrete-Time Stochastic Processes
2.8　Sspatial Stochastic Processes
2.9　Random Signals
2.10　 Bibliographical Notes
2.11　 Problems
Chapter 3　Signal Representations and Statistics
3.1　Chapter Highlights
3.2　Relationship of Power Spectral Density and Autocorrelation Functi
3.3　Sampling Theorem
3.4　Linear Time-Invariant and Linear Shift-Invariant Systems
3.5　Bandpass Signal Representations
3.6　Bibliographical Notes
3.7　Problems
Part Ⅱ　Detection Chapters
Chapter 4　Single Sample Detection of Binary Hypotheses
4.1　Chapter Highlights
4.2　Hypothesis Testing and the MAP Criterion
4.3　Bayes Criterion
4.4　Minimax Criterion
4.5　Neyman-Pearson Criterion
4.6　Summary of Detection-Criterion Results Used in Chapter 4 Examples
4.7　Sequential Detection
4.8　Bibliographical Notes
4.9　Problems
Chapter 5　Multiple Sample Detection of Binary Hypotheses
5.1　Chapter Highlights
5.2　Examples of Multiple Measurements
5.3　Bayes Criterion
5.4　Other Criteria
5.5　The Optimum Digital Detector in Additive Gaussian Noise
5.6　Filtering Alternatives
5.7　Continuous Signals　White Gaussian Noise
5.8　Continuous Signals　Colored Gaussian Noise
5.9　Performance of Binary Receivers in AWGN
5.10　 Further Receiver-Structure Considerations
5.11　 Sequential Detection and Performance
……
Part Ⅲ　Estimation Chapters
Part Ⅳ　Application Chapters
Appendix A　Properties of Distribution and Density Functions
Appendix B　Common pdfs,cdfs, and characteristic Functions
Appendix C　Multiple Normal Random Variables
Appendix D　Properties of Autocorrelation and Power Spectral Density
Appendix E　Equivalence of LTI and LSI Bandlimited Systems
Appendix F　Theory of Random Sums
Appendix G　Evaluations Useful for Chapters6,7,and 16
Appendix H　Gram-Charlier Type Series
Appendix I　Mobile User Detection
Bibliography
Glossary
List of Symbols
Index