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least-squares identification algorithm

Combined state and parameter estimation for Hammerstein systems with time-delay using the Kalman filtering

Combined state and parameter estimation for Hammerstein systems with time-delay using the Kalman filtering

... the identification of Hammerstein ...improved least squares identification algorithm for multivariable Hammerstein output error moving average systems by using the Taylor expansion on a ...

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Least squares-based iterative identification methods for linear-in-parameters systems using the decomposition technique

Least squares-based iterative identification methods for linear-in-parameters systems using the decomposition technique

... The least squares identification method involves matrix inversion and its computational complex- ity depends on the dimensions of the covariance matrices ...based least squares ...

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A Partial Least Squares based algorithm for parsimonious variable selection

A Partial Least Squares based algorithm for parsimonious variable selection

... For identification of codon variations that distinguishes different bacterial taxa to be utilized as classifiers in metagenomic analysis, 11 models, representing each phylum, were considered ...

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Identification of nonlinear systems with non-persistent excitation using an iterative forward orthogonal least squares regression algorithm

Identification of nonlinear systems with non-persistent excitation using an iterative forward orthogonal least squares regression algorithm

... OFR algorithm, the terms are selected into the model one at a ...regression algorithm has been introduced to improve the suboptimal problem where a small modification to the term selection procedure has ...

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Current identification in vacuum circuit breakers as a least squares problem*

Current identification in vacuum circuit breakers as a least squares problem*

... the least squares solution of a system of equations where the system matrix is generally rectangular (more unknowns than equations or viceversa) and frequently rank ...linear least-squares ...

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Data filtering-based least squares iterative algorithm for Hammerstein nonlinear systems by using the model decomposition

Data filtering-based least squares iterative algorithm for Hammerstein nonlinear systems by using the model decomposition

... system identification and parameter esti- mation for linear or nonlinear dynamics ...likelihood identification method for Wiener models ...parameter identification problem of nonlinear dynamic sys- ...

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Ultra-Orthogonal Forward Regression Algorithms for the Identification of Non-Linear Dynamic Systems

Ultra-Orthogonal Forward Regression Algorithms for the Identification of Non-Linear Dynamic Systems

... Ultra Least Squares (ULS) criterion is introduced for system ...standard least squares criterion which is based on the Euclidean norm of the residuals, the new ULS criterion is derived from ...

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Application of structured total least squares for system identification and model reduction

Application of structured total least squares for system identification and model reduction

... alternating least squares method is ...Gauss–Newton algorithm is ...Levenberg-Marquardt algorithm is ...latter algorithm can be found in Appendix A, where a software package for solving ...

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Application of structured total least squares for system identification and model reduction

Application of structured total least squares for system identification and model reduction

... Initially the purpose of the simulation example was to show that the STLS method can be used as an “iterative refine- ment step” of subspace identification methods. For this purpose, we were interested in the time ...

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Person re identification using partial least squares appearance modelling

Person re identification using partial least squares appearance modelling

... Weighted LOMO We modify LOMO [10] such that foreground regions are prioritised over background by feature weighting. LOMO begins by applying a colour normalisa- tion step using the Retinex algorithm [8] to make ...

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Identification of MIMO Hammerstein models using Singular Value Decomposition approach

Identification of MIMO Hammerstein models using Singular Value Decomposition approach

... In this paper, we present a new approach to identify multivariable Hammerstein systems based on the Singular Value Decomposition (SVD) method. The technique allows for the determination of the memoryless static ...

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Sparse kernel regression modelling using combined locally regularized orthogonal least squares and D optimality experimental design

Sparse kernel regression modelling using combined locally regularized orthogonal least squares and D optimality experimental design

... nonlinear identification algorithm by combining a locally regularized orthogonal least squares (LROLS) model selection with a D-optimality experimental ...proposed algorithm aims to ...

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Least Squares Matrix Algorithm for State Space Modelling of Dynamic Systems

Least Squares Matrix Algorithm for State Space Modelling of Dynamic Systems

... The validity of the LSM algorithm was warranted in the analysis of neuroelectric signal waveforms. The neur- oelectric signals were recorded from two different loca- tions of the brain in freely behaving ...

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A Robust Collaborative Recommendation Algorithm Based on Least Median Squares Estimator

A Robust Collaborative Recommendation Algorithm Based on Least Median Squares Estimator

... LMedSMF algorithm, we conduct experiments on the MovieLens 100K dataset and compare LMedSMF with M-estimator based matrix factorization (MMF) and LTS-estimator based matrix factorization (LTSMF) in terms of ...

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Newton Krylov Type Algorithm for Solving Nonlinear Least Squares Problems

Newton Krylov Type Algorithm for Solving Nonlinear Least Squares Problems

... is performed. If there is a satisfactory reduction, then the step can be taken, or a possibly larger trust region used. If not, then the trust region is reduced and the inner iteration is repeated. For now, we leave ...

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Predicting bruise susceptibility in apples using Vis/SWNIR technique combined with ensemble learning

Predicting bruise susceptibility in apples using Vis/SWNIR technique combined with ensemble learning

... partial least squares model (PLS), partial least squares model combined with successful projection algorithm (SPA-PLS), and selective ensemble learning based on feature selection ...

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A general order multichannel, fast least squares algorithm with telecommunications applications

A general order multichannel, fast least squares algorithm with telecommunications applications

... It was derived using the recursive form of (2.6) and the matrix inversion lemma [52), which generates an explicit inverse formula for matrices of a certain type. The algorithm sequence i[r] ...

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Recursive Least Squares Dictionary Learning Algorithm for Electrical Impedance Tomography

Recursive Least Squares Dictionary Learning Algorithm for Electrical Impedance Tomography

... reconstruction algorithm by alternating the process of image reconstruction and dictionary ...Recursive Least Squares Dictionary Learning Algorithm (RLS-DLA) is used to learn the initial ...

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Least Squares Filtering Algorithm for Reactive Near Field Probe Correction

Least Squares Filtering Algorithm for Reactive Near Field Probe Correction

... In this work, we solve this problem by an inverse filtering approach that integrates the statistical characteristics of noise using the constrained least squares filtering technique (CLSF) [10]. This method ...

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Object Detection and Tracking Using Uncalibrated Cameras

Object Detection and Tracking Using Uncalibrated Cameras

... The work presented in this thesis deals with the estimation of the 3D position of an object from stereo images. The problem is decomposed into a number of tasks, each task being associated with a specific geometric ...

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