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Table of Contents

1 Review.- 1 Review of Concepts in Probability.- 2 Random Noise Generation.- 1 Random Noise Generation.- 2 Cholesky Decomposition.- 3 Uses of the Pseudo Inverse.- 4 Signal Models.- 5 Sensor Model.- 3 Historical Background.- 1 Background Material.- 2 Historical Developments for Filtering.- 3 Development of Innovations.- 4 Sequential Filter Development.- 4 Sequential Filtering Theory.- 1 Summary of the Sequential Filter.- 2 The Scalar Autonomous Riccati Equation.- 3 Linearizing the Riccati Equation.- 5 Burg Technique.- 1 Background Material.- 6 Signal Processing.- 1 The Burg Technique.- 2 Signal Processing.- 3 Burg Revisited (Rouché’s Theorem).- 7 Classical Approach.- 1 Classical Steady-State Filtering.- 8 A Priori Bounds.- 1 A Priori Bounds for the Riccati Equation.- 2 Information and Filtering.- 3 Nonlinear Systems.- 9 Asymptotic Theory.- 1 Applications of the Theory of Filtering.- 2 Asymptotic Theory of the Riccati Equation.- 3 Steady-State Solution to Riccati.- 10 Advanced Topics.- 1 Invariant Directions.- 2 Nonlinear Filtering.- 11 Applications.- 1 Historical Applications.- 12 Phase Tracking.- 1 The Phase Lock Loop.- 2 Phase Demodulation.- 13 Device Synthesis.- 1 Device Synthesis for Nonlinear Filtering.- 2 Radar Filtering Application.- 14 Random Fields.