Orthogonal least squares methods and their application to non-linear system identification
TLDR
Identification algorithms based on the well-known linear least squares methods of gaussian elimination, Cholesky decomposition, classical Gram-Schmidt, modified Gram- Schmidt, Householder transformation, Givens method, and singular value decomposition are reviewed.Abstract:
Identification algorithms based on the well-known linear least squares methods of gaussian elimination, Cholesky decomposition, classical Gram-Schmidt, modified Gram-Schmidt, Householder transformation, Givens method, and singular value decomposition are reviewed. The classical Gram-Schmidt, modified Gram-Schmidt, and Householder transformation algorithms are then extended to combine structure determination, or which terms to include in the model, and parameter estimation in a very simple and efficient manner for a class of multivariate discrete-time non-linear stochastic systems which are linear in the parameters.read more
Citations
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Proceedings ArticleDOI
Modelling of melt pressure development in polymer extrusion: Effects of process settings and screw geometry
TL;DR: In this paper, a nonlinear static and linear dynamic model was developed to explore the effects of process settings and screw geometry on melt pressure development in a single screw extrusion, and a computationally efficient linear-in-the-parameters modelling technique was used in model development and the resultant models show satisfactory performance in predicting the melt pressure with good accuracy over a wide operating window.
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Fuzzy adaptive control of a certain class of SISO discrete-time processes
TL;DR: This manuscript addresses the problem of the stability of a certain class of SISO discrete-time processes controlled by an adaptive fuzzy controller by using Lyapunov stability theory, and argues that this gradient-based adaptation law can be simplified dramatically.
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Extended analysis of bpso structure selection of nonlinear auto-regressive model with exogenous inputs (NARX) of direct current motor
TL;DR: The results show that the BPSO structure selection method is improved by the presence of the database, while the magnitude scaling approach was the best preprocessing method for NARX identification of the DCM dataset.
Book ChapterDOI
Numerical Simulation of Wind Effects
Ahsan Kareem,Megan McCullough +1 more
TL;DR: A historical perspective, recent developments, and future challenges for simulation are summarized, which include methods based on the time, frequency, and time-frequency domains employed for data and response analysis.
A continuation approach to estimate a solution path of mixed L2-L0 minimization problems
TL;DR: The heuristic Single Best Replacement (SBR) algorithm is proposed, inspired by the Single Most likely replacement (SMLR) algorithm, and extended to a continuation version estimating a whole solution path, i.e., a series of solutions depending on the level of sparsity.
References
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Book
Applied Regression Analysis
Norman R. Draper,Harry Smith +1 more
TL;DR: In this article, the Straight Line Case is used to fit a straight line by least squares, and the Durbin-Watson Test is used for checking the straight line fit.
Journal ArticleDOI
Singular value decomposition and least squares solutions
Gene H. Golub,C. Reinsch +1 more
TL;DR: The decomposition of A is called the singular value decomposition (SVD) and the diagonal elements of ∑ are the non-negative square roots of the eigenvalues of A T A; they are called singular values.
Book
Linear regression analysis
TL;DR: In this paper, the authors take into serious consideration the further development of regression computer programs that are efficient, accurate, and considered an important part of statistical research, and provide up-to-date accounts of computational methods and algorithms currently in use without getting entrenched in minor computing details.
Journal ArticleDOI
Input-output parametric models for non-linear systems Part II: stochastic non-linear systems
TL;DR: Recursive input-output models for non-linear multivariate discrete-time systems are derived, and sufficient conditions for their existence are defined.