This article reviews and investigates several basic recursive parameter identification
methods for a general stochastic system with colored noise (ie, output-error autoregressive …

Least squares is an important method for solving linear fitting problems and quadratic
optimization problems. This paper explores the properties of the least squares methods and …

This paper focuses on the identification of a multivariable controlled autoregressive-like
(CAR-like) system. A joint identification algorithm of stochastic gradient and least squares is …

Adaptive control is a control methodology capable of dealing with uncertain systems to
ensure desired control performance. This paper provides an overview of some fundamental …

In this note, we apply a hierarchical identification principle to study solving the Sylvester and
Lyapunov matrix equations. In our approach, we regard the unknown matrix to be solved as …

This communique uses the auxiliary model method to study the identification problem of a
multiple-input multiple-output (MIMO) system. For such a MIMO system whose outputs are …

This paper derives the input‐output representation of the dynamical system described by a
linear multivariable state‐space model and the corresponding multivariate linear regressive …

Two identification algorithms, an iterative least-squares and a recursive least-squares, are
developed for Hammerstein nonlinear systems with memoryless nonlinear blocks and linear …

In this paper, by extending the well-known Jacobi and Gauss–Seidel iterations for Ax= b, we
study iterative solutions of matrix equations AXB= F and generalized Sylvester matrix …

This paper considers the identification problems of the Hammerstein nonlinear systems. A
projection and a stochastic gradient (SG) identification algorithms are presented for the …