| Preface | p. xiii |
| Conventions | p. xv |
| Glossary of Symbols | p. xvii |
| Overview | p. 1 |
| Introduction | p. 3 |
| Motivating Examples | p. 4 |
| System Identification with Quantized Observations | p. 7 |
| Outline of the Book | p. 8 |
| System Settings | p. 13 |
| Basic Systems | p. 14 |
| Quantized Output Observations | p. 16 |
| Inputs | p. 17 |
| System Configurations | p. 18 |
| Filtering and Feedback Configurations | p. 19 |
| Systems with Communication Channels | p. 19 |
| Uncertainties | p. 20 |
| System Uncertainties: Unmodeled Dynamics | p. 20 |
| System Uncertainties: Function Mismatch | p. 21 |
| Sensor Bias and Drifts | p. 21 |
| Noise | p. 21 |
| Unknown Noise Characteristics | p. 22 |
| Communication Channel Uncertainties | p. 22 |
| Notes | p. 22 |
| Stochastic Methods for Linear Systems | p. 23 |
| Empirical-Measure-Based Identification | p. 25 |
| An Overview of Empirical-Measure-Based Identification | p. 26 |
| Empirical Measures and Identification Algorithms | p. 29 |
| Strong Convergence | p. 32 |
| Asymptotic Distributions | p. 34 |
| Mean-Square Convergence | p. 37 |
| Convergence under Dependent Noise | p. 41 |
| Proofs of Two Propositions | p. 43 |
| Notes | p. 46 |
| Estimation Error Bounds: Including Unmodeled Dynamics | p. 49 |
| Worst-Case Probabilistic Errors and Time Complexity | p. 50 |
| Upper Bounds on Estimation Errors and Time Complexity | p. 50 |
| Lower Bounds on Estimation Errors | p. 53 |
| Notes | p. 56 |
| Rational Systems | p. 59 |
| Preliminaries | p. 59 |
| Estimation of xk | p. 60 |
| Estimation of Parameter | p. 62 |
| Parameter Identifiability | p. 62 |
| Identification Algorithms and Convergence Analysis | p. 65 |
| Notes | p. 66 |
| Quantized Identification and Asymptotic Efficiency | p. 67 |
| Basic Algorithms and Convergence | p. 68 |
| Quasi-Convex Combination Estimators (QCCE) | p. 70 |
| Alternative Covariance Expressions of Optimal QCCEs | p. 72 |
| Cramér-Rao Lower Bounds and Asymptotic Efficiency of the Optimal QCCE | p. 75 |
| Notes | p. 79 |
| Input Design for Identification in Connected Systems | p. 81 |
| Invariance of Input Periodicity and Rank in Open- and Closed-Loop Configurations | p. 82 |
| Periodic Dithers | p. 83 |
| Sufficient Richness Conditions under Input Noise | p. 85 |
| Actuator Noise | p. 88 |
| Notes | p. 91 |
| Identification of Sensor Thresholds and Noise Distribution Functions | p. 95 |
| Identification of Unknown Thresholds | p. 95 |
| Sufficient Richness Conditions | p. 96 |
| Recursive Algorithms | p. 99 |
| Parameterized Distribution Functions | p. 99 |
| Joint Identification Problems | p. 101 |
| Richness Conditions for Joint Identification | p. 101 |
| Algorithms for Identifying System Parameters and Distribution Functions | p. 103 |
| Convergence Analysis | p. 105 |
| Recursive Algorithms | p. 106 |
| Recursive Schemes | p. 107 |
| Asymptotic Properties of Recursive Algorithm (8.14) | p. 108 |
| Algorithm Flowcharts | p. 111 |
| Illustrative Examples | p. 113 |
| Notes | p. 115 |
| Deterministic Methods for Linear Systems | p. 117 |
| Worst-Case Identification | p. 119 |
| Worst-Case Uncertainty Measures | p. 120 |
| Lower Bounds on Identification Errors and Time Complexity | p. 121 |
| Upper Bounds on Time Complexity | p. 124 |
| Identification of Gains | p. 127 |
| Identification Using Combined Deterministic and Stochastic Methods | p. 135 |
| Identifiability Conditions and Properties under Deterministic and Stochastic Frameworks | p. 136 |
| Combined Deterministic and Stochastic Identification Methods | p. 139 |
| Optimal Input Design and Convergence Speed under Typical Distributions | p. 141 |
| Notes | p. 145 |
| Worst-Case Identification Using Quantized Observations | p. 149 |
| Worst-Case Identification with Quantized Observations | p. 150 |
| Input Design for Parameter Decoupling | p. 151 |
| Identification of Single-Parameter Systems | p. 153 |
| General Quantization | p. 154 |
| Uniform Quantization | p. 159 |
| Time Complexity | p. 163 |
| Examples | p. 165 |
| Notes | p. 168 |
| Identification of Nonlinear and Switching Systems | p. 171 |
| Identification of Wiener Systems | p. 173 |
| Wiener Systems | p. 174 |
| Basic Input Design and Core Identification Problems | p. 175 |
| Properties of Inputs and Systems | p. 177 |
| Identification Algorithms | p. 179 |
| Asymptotic Efficiency of the Core Identification Algorithms | p. 184 |
| Recursive Algorithms and Convergence | p. 188 |
| Examples | p. 190 |
| Notes | p. 194 |
| Identification of Hammerstein Systems | p. 197 |
| Problem Formulation | p. 198 |
| Input Design and Strong-Full-Rank Signals | p. 199 |
| Estimates of with Individual Thresholds | p. 202 |
| Quasi-Convex Combination Estimators of | p. 204 |
| Estimation of System Parameters | p. 212 |
| Examples | p. 218 |
| Notes | p. 222 |
| Systems with Markovian Parameters | p. 225 |
| Markov Switching Systems with Binary Observations | p. 227 |
| Wonham-Type Filters | p. 227 |
| Tracking: Mean-Square Criteria | p. 229 |
| Tracking Infrequently Switching Systems: MAP Methods | p. 237 |
| Tracking Fast-Switching Systems | p. 242 |
| Long-Run Average Behavior | p. 243 |
| Empirical Measure-Based Estimators | p. 245 |
| Estimation Errors on Empirical Measures: Upper and Lower Bounds | p. 249 |
| Notes | p. 252 |
| Complexity Analysis | p. 253 |
| Complexities, Threshold Selection, Adaptation | p. 255 |
| Space and Time Complexities | p. 256 |
| Binary Sensor Threshold Selection and Input Design | p. 259 |
| Worst-Case Optimal Threshold Design | p. 261 |
| Threshold Adaptation | p. 264 |
| Quantized Sensors and Optimal Resource Allocation | p. 267 |
| Discussions on Space and Time Complexity | p. 271 |
| Notes | p. 272 |
| Impact of Communication Channels | p. 275 |
| Identification with Communication Channels | p. 276 |
| Monotonicity of Fisher Information | p. 277 |
| Fisher Information Ratio of Communication Channels | p. 278 |
| Vector-Valued Parameters | p. 280 |
| Relationship to Shannon's Mutual Information | p. 282 |
| Tradeoff between Time Information and Space Information | p. 283 |
| Interconnections of Communication Channels | p. 284 |
| Notes | p. 285 |
| Background Materials | p. 287 |
| Martingales | p. 287 |
| Markov Chains | p. 290 |
| Weak Convergence | p. 299 |
| Miscellany | p. 302 |
| References | p. 305 |
| Index | p. 315 |
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