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Published: July 9, 2014 by CRC Press
Content: 429 Pages | 75 Illustrations
Author(s): Han-Fu Chen, Wenxiao Zhao

Recursive Identification and Parameter Estimation

Table of Contents

Dependent Random Vectors 
Some Concepts of Probability Theory 
Independent Random Variables, Martingales, and Martingale Difference Sequences 
Markov Chains with State Space (Rm;Bm)
Mixing Random Processes 
Stationary Processes
Notes and References

Recursive Parameter Estimation 
Parameter Estimation as Root-Seeking for Functions
Classical Stochastic Approximation Method: RM Algorithm
Stochastic Approximation Algorithm with Expanding Truncations 
SAAWET with Nonadditive Noise
Linear Regression Functions 
Convergence Rate of SAAWET
Notes and References 

Recursive Identification for ARMAX Systems
LS and ELS for Linear Systems
Estimation Errors of LS/ELS
Hankel Matrices Associated with ARMA
Coefficient Identification of ARMAX by SAAWET
Order Estimation of ARMAX
Multivariate Linear EIV Systems
Notes and References

Recursive Identification for Nonlinear Systems
Recursive Identification of Hammerstein Systems
Recursive Identification of Wiener Systems
Recursive Identification of Wiener–Hammerstein Systems
Recursive Identification of EIV Hammerstein Systems
Recursive Identification of EIV Wiener Systems
Recursive Identification of Nonlinear ARX Systems
Notes and References

Other Problems Reducible to Parameter Estimation 
Principal Component Analysis
Consensus of Networked Agents
Adaptive Regulation for Hammerstein and Wiener Systems
Convergence of Distributed Randomized PageRank Algorithms
Notes and References


Proof of Some Theorems in Chapter 1
Nonnegative Matrices


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