1. 1 Classification and modeling methods of system mathematical models

1.2 Definition, content and steps of identification

Common error criteria in 1.3 identification

1.4 system identification classification

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Chapter 2 System Identification of Common Input Signals

2. 1 system identification input signal selection criteria

2.2 white noise and its generation method

2.3 Pseudo-random binary sequence-the generation and properties of M sequence

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The third chapter is the classical identification method of linear systems.

3. 1 Identification of Impulse Response of Linear System by M Sequence

3.2 Using impulse response to find transfer function

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Chapter IV Normative Expression of Dynamic System

4. 1 savings principle

4.2 Representation of difference equation and state equation of linear system

4.3 Deterministic Regular Equation of State

4.4 Deterministic canonical difference equation

4.5 Stochastic Regular Equation of State

4.6 Stochastic Regular Difference Equation

4.7 Prediction error equation

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Chapter 5 Identification by Least Square Method

5. 1 least square method

5.2 Least Square Method for Matrix-free Inversion

5.3 recursive least squares method

5.4 auxiliary variable method

5.5 Recursive auxiliary variable method

5.6 Generalized Least Squares Method

5.7 Alternating Generalized Least Squares (Xiafa)

5.8 Augmented Matrix Method

5.9 Multistage Least Squares Method

5. 10 Fast Multistage Least Squares Method

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Chapter 6 Maximum Likelihood Identification

6. 1 maximum likelihood identification method

6.2 recursive maximum likelihood method

6.3 Accuracy of parameter estimation

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Chapter VII Identification Method of Time-varying Parameters

7. 1 forgetting factor method, rectangular window method and Kalman filter method

7.2 Time-varying parameter identification method for automatically adjusting forgetting factor

7.3 Identification method of approximate time-varying parameters of broken line segment

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Chapter 8 Identification of Multi-input-Multi-input System

Chapter IX Other Identification Methods

10 Chapter Establishment of Random Time Series Model

Chapter 1 1 System Structure Identification

Chapter 12 closed-loop system identification

Chapter 13 Application of System Identification in Aircraft Parameter Identification

Chapter 14 Application of Neural Network in System Identification

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