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List of Figures
List of Tables
Part I: Preliminaries
Chapter 1: Introduction
1.1 Bayesian Inference
1.2 Bayesian Hierarchy of Estimation Methods
1.3 Scope of this Text
1.4 Modeling and Simulation with Matlab®
Chapter 2: Preliminary Mathematical Concepts
2.1 A Very Brief Overview of Matrix Linear Algebra
2.2 Vector Point Generators
2.3 Approximating Nonlinear Multidimensional Functions with Multidimensional Arguments
2.4 Overview of Multivariate Statistics
Chapter 3: General Concepts of Bayesian Estimation
3.1 Bayesian Estimation
3.2 Point Estimators
3.3 Introduction to Recursive Bayesian Filtering of Probability Density Functions
3.4 Introduction to Recursive Bayesian Estimation of the State Mean and Covariance
3.5 Discussion of General Estimation Methods
Chapter 4: Case Studies: Preliminary Discussions
4.1 The Overall Simulation/Estimation/Evaluation Process
4.2 A Scenario Simulator for Tracking a Constant Velocity Target Through a DIFAR Buoy Field
4.3 DIFAR Buoy Signal Processing
4.4 The DIFAR Likelihood Function
Part II: The Gaussian Assumption: A Family of Kalman Filter Estimators
Chapter 5: The Gaussian Noise Case: Multidimensional Integration of Gaussian-Weighted Distributions
5.1 Summary of Important Results From Chapter 3
5.2 Derivation of the Kalman Filter ...
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