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Chapter 1. Bias
Chapter 2. Classical System Identification
Chapter 3. Regularization of Linear Regression Models
Chapter 4. Bayesian Interpretation of Regularization
Chapter 5. Regularization for Linear System Identification
Chapter 6. Regularization in Reproducing Kernel Hilbert Spaces
Chapter 7. Regularization in Reproducing Kernel Hilbert Spaces for Linear System Identification
Chapter 8. Regularization for Nonlinear System Identification
Chapter 9. Numerical Experiments and Real-World Cases.

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