Hidden Markov Models and Dynamical Systems
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Preface 1. Introduction 2. Basic algorithms 3. Variants and generalizations 4. Continuous states and observations and Kalman filtering 5. Performance bounds and a toy problem 6. Obstructive sleep apnea Appendix A. Formulas for matrices and Gaussians Appendix B. Notes on software Bibliography Index.