Chapter 5. System Identification: The Bases

5.1 System Model Identification Principles

5.2 Algorithms for Parameter Estimation

5.2.1 Introduction

5.2.2 Gradient Algorithm

5.2.3 Least Squares Algorithm

5.2.4 Choice of the Adaptation Gain

5.3 Choice of the Input Sequence for System Identification

5.3.1 The Problem

5.3.2 Pseudo Random Binary Sequences (PRBS)

5.4 Effects of Random Disturbances upon Parameter Estimation

5.5 Structure of Recursive Identification Methods

5.6 Concluding Remarks

5.7 Notes and References