Table of Contents
Signal Processing at Your Fingertips!
Section 1: Statistical Signal Processing
Chapter 1. Introduction to Statistical Signal Processing
3.01.1 A brief historical recount
3.01.4 Suggested further reading
Chapter 2. Model Order Selection
3.02.2 Example: variable selection in regression
3.02.3 Methods based on statistical inference paradigms
3.02.4 Information and coding theory based methods
3.02.5 Example: estimating number of signals in subspace methods
Chapter 3. Non-Stationary Signal Analysis Time-Frequency Approach
3.03.2 Linear signal transforms
3.03.3 Quadratic time-frequency distributions
3.03.4 Higher order time-frequency representations
3.03.5 Processing of sparse signals in time-frequency
3.03.6 Examples of time-frequency analysis applications
Chapter 4. Bayesian Computational Methods in Signal Processing
3.04.4 State-space models and sequential inference
A Probability densities and integrals
Chapter 5. Distributed Signal Detection
3.05.2 Distributed detection with independent observations
3.05.3 Distributed detection with dependent observations
Chapter 6. Quickest Change Detection
3.06.2 Mathematical preliminaries
3.06.3 Bayesian quickest change detection
3.06.4 Minimax quickest change detection
3.06.5 Relationship between the models
3.06.6 Variants and generalizations of the quickest change detection problem
3.06.7 Applications of quickest change detection
3.06.8 Conclusions and future directions
Chapter 7. Geolocation—Maps, Measurements, Models, and Methods
Chapter 8. Performance Analysis and Bounds
3.08.2 Parametric statistical models
3.08.3 Maximum likelihood estimation and the CRB
3.08.4 Mean-square error bound
3.08.5 Perturbation methods for algorithm analysis
3.08.6 Constrained Cramér-Rao bound and constrained MLE
3.08.7 Multiplicative and non-Gaussian noise
3.08.8 Asymptotic analysis and the central limit theorem
3.08.9 Asymptotic analysis and parametric models
Chapter 9. Diffusion Adaptation Over Networks
3.09.2 Mean-square-error estimation
3.09.3 Distributed optimization via diffusion strategies
3.09.4 Adaptive diffusion strategies
3.09.5 Performance of steepest-descent diffusion strategies
3.09.6 Performance of adaptive diffusion strategies
3.09.7 Comparing the performance of cooperative strategies
3.09.8 Selecting the combination weights
3.09.9 Diffusion with noisy information exchanges
3.09.10 Extensions and further considerations
Section 2: Array Signal Processing
Chapter 10. Array Signal Processing: Overview of the Included Chapters
3.10.2 Summary of the included chapters
Chapter 11. Introduction to Array Processing
3.11.3 Spatial filtering and beam patterns
3.11.4 Beam forming and signal detection
3.11.5 Direction-of-arrival estimation
3.11.6 Non-coherent array applications
Chapter 12. Adaptive and Robust Beamforming
3.12.2 Data and beamforming models
3.12.4 Robust adaptive beamforming
Chapter 13. Broadband Beamforming and Optimization
3.13.2 Environment and channel modeling
3.13.3 Broadband beamformer design in element space
3.13.4 Broadband beamformer design using the wave equation
3.13.5 Optimum and adaptive broadband beamforming
Chapter 14. DOA Estimation Methods and Algorithms
3.14.6 Wideband DOA estimation
Chapter 15. Subspace Methods and Exploitation of Special Array Structures
3.15.4 Subspace-based algorithms
Chapter 16. Performance Bounds and Statistical Analysis of DOA Estimation
3.16.2 Models and basic assumption
3.16.3 General statistical tools for performance analysis of DOA estimation
3.16.4 Asymptotic distribution of estimated DOA
3.16.5 Detection of number of sources
3.16.6 Resolution of two closely spaced sources
Chapter 17. DOA Estimation of Nonstationary Signals
3.17.2 Nonstationary signals and time-frequency representations
3.17.3 Spatial time-frequency distribution
3.17.4 DOA estimation techniques
3.17.5 Joint DOD/DOA estimation in MIMO radar systems
Chapter 18. Source Localization and Tracking
3.18.4 Signal propagation models
3.18.5 Source localization algorithms
3.18.6 Target tracking algorithm
Chapter 19. Array Processing in the Face of Nonidealities
3.19.2 Ideal array signal models
3.19.3 Examples of array nonidealities
3.19.5 Model-driven techniques
3.19.8 Array processing examples
Chapter 20. Applications of Array Signal Processing
3.20.1 Introduction and background
3.20.4 Positioning and navigation
3.20.5 Wireless communications