This unified survey focuses on linear discrete-time systems and explores the natural extensions to nonlinear systems. In keeping with the importance of computers to practical applications, the authors emphasize discrete-time systems. Their approach summarizes the theoretical and practical aspects of a large class of adaptive algorithms. 1984 edition.
This unified survey focuses on linear discrete-time systems and explores the natural extensions to nonlinear systems. In keeping with the importance of computers to practical applications, the authors emphasize discrete-time systems. Their approach summarizes the theoretical and practical aspects of a large class of adaptive algorithms. 1984 edition.
Preface 1. Introduction to Adaptive Techniques Part 1. Deterministic Systems 2. Models for Deterministic Dynamical Systems 3. Parameter Estimation for Deterministic Systems 4. Deterministic Adaptive Prediction 5. Control of Linear Deterministic Systems 6. Adaptive Control of Linear Deterministic Systems Part 2. Stochastic Systems 7. Optimal Filtering and Prediction 8. Parameter Estimation for Stochastic Dynamic Systems 9. Adaptive Filtering and Prediction 10. Control of Stochastic Systems 11. Adaptive Control of Stochastic Systems Appendices A. A Brief Review of Some Results from Systems Theory B. A Summary of Some Stability Results C. Passive Systems Theory D. Probability Theory and Stochastic Processes E. Matrix Riccati Equations References Index
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