Cargando…
Detection of signals in noise.
The Second Edition is an updated revision to the authors highly successful and widely used introduction to the principles and application of the statistical theory of signal detection. This book emphasizes those theories that have been found to be particularly useful in practice including principles...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
San Diego :
Academic Press,
©1995.
|
| Edición: | 2nd ed. / |
| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Front Cover; Detection of Signals in Noise; Copyright Page; Dedication; Table of Contents; Preface; Chapter 1. Probability; 1.1 Probability in Brief; 1.2 Conditional Probability and Statistical Independence; 1.3 Probability Distribution Functions; 1.4 Continuous Random Variables; 1.5 Functions of Random Variables; 1.6 Characteristic Functions; 1.7 Expectation and Moments; 1.8 Complex Random Variables; Exercises; Chapter 2. Random Processes; 2.1 Introduction; 2.2 Relation to Probability; 2.3 Ensemble Correlation Functions; 2.4 Time Averages; 2.5 Power Spectral Density.
- 2.6 Response of Linear FiltersExercises; Chapter 3. Narrowband Signals; 3.1 The Analytic Signal; 3.2 Narrowband Signals; 3.3 Hilbert Transform; 3.4 Narrowband Filters; 3.5 Narrowband Processes; 3.6 Determination of the Complex Envelope; 3.7 Fourier Series Representation; Exercises; Chapter 4. Gaussian Derived Processes; 4.1 The Gaussian Probability Density; 4.2 The Central Limit Theorem; 4.3 Sum of a Sine Wave and a Gaussian Process; 4.4 Distribution of the Envelope of a Narrowband Process; 4.5 Envelope of a Narrowband Signal Plus Narrowband Noise.
- 4.6 Squared Envelope of a Narrowband Noise Process4.7 The Chi-Squared Density; 4.8 Squared Envelope of a Sine Wave Plus a Narrowband Process; 4.9 Noncentral Chi-Squared Density; 4.10 Student's t-Density; 4.11 Snedecor's F-Density; Exercises; Chapter 5. Hypothesis Testing; 5.1 Introduction; 5.2 A Simple Detection Problem; 5.3 The Neyman-Pearson Criterion; 5.4 Bayes' Criterion; 5.5 Minimum Error Probability Criterion; 5.6 Minimax Criterion; 5.7 Multiple Measurements; 5.8 Multiple Alternative Hypothesis Testing; 5.9 Composite Hypothesis Testing with Minimum Cost; 5.10 Sufficient Statistics.
- 5.11 Uniformly Most Powerful Tests5.12 Unknown a Priori Information and Nonoptimal Tests; Exercises; Chapter 6. Detection of Known Signals; 6.1 Two Completely Known Signals in Additive Gaussian Noise; 6.2 Application to Radar; 6.3 Application to Binary Communications; 6.4 The Likelihood Functions; 6.5 Matched Filters; 6.6 The General Discrete Matched Filter; 6.7 An m-ary Communication System; 6.8 The General Discrete Gaussian Problem; Exercises; Chapter 7. Detection of Signals with Random Parameters; 7.1 Processing Narrowband Signals; 7.2 Detection of Signals with Unknown Carrier Phase.
- 7.3 The Quadrature Receiver and Equivalent Forms7.4 Receiver Operating Characteristics; 7.5 Signals with Random Phase and Amplitude; 7.6 Noncoherent Frequency Shift Keying; 7.7 Signals with Random Frequency; 7.8 Signals with Random Time of Arrival; Exercises; Chapter 8. Multiple Pulse Detection of Signals; 8.1 Known Signals; 8.2 Signals with Unknown Phase; 8.3 Performance of the Quadratic Detector; 8.4 Gram-Charlier Series; 8.5 Performance of the Linear Detector; 8.6 The Case of Unknown Phase and Known Unequal Amplitudes; 8.7 Unknown Amplitude and Phase; 8.8 Diversity Reception; Appendix 1.