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Least-Squares Estimation
Least-squares estimation provides a means of determining estimates of model parameters that are optimal in the sense of minimizing the sum of the...
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The posterior selection method for hyperparameters in regularized least squares method
The selection of hyperparameters in regularized least squares plays an important role in large-scale system identification. The traditional methods...
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A Fuzzy Convex Nonparametric Least Squares Method with Different Shape Constraints
The main drawback of the typical fuzzy least squares approach is that the resulting fuzzy regression model is linear, and the model's accuracy...
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Least Squares Smoothing of Nonlinear Systems
We consider the fixed interval smoothing problem for data from linear or nonlinear models where there is a priori information about the boundary...
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Least Squares Optimization
The last chapter concluded with a nonlinear least squares formulation of the (full) SLAM problem and provided an intuitive analogy that helps to...
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Distributed Adaptive Thresholding Graph Recursive Least Squares Algorithm
In this paper, we present a novel approach for the reconstruction of sparse graph signals using a distributed adaptive thresholding recursive least...
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The Optimal Regularized Weighted Least-Squares Method for Impulse Response Estimation
The system identification literature has been going through a recent paradigm change with the emergent use of regularization and kernel-based...
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Weighted Tensor Least Angle Regression for Solving Sparse Weighted Multilinear Least Squares Problems
Sparse weighted multilinear least-squares is a generalization of the sparse multilinear least-squares problem, where prior information about, e.g.,...
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High Order Nonlinear Least-Squares for Satellite Pose Estimation
This paper introduces a high-order nonlinear least-squares method for solving six-degree-of-freedom (6-DOF) navigation of satellite maneuvers. The...
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Least-Squares Algorithms for Complex-Valued Blind Source Separation
Blind source separation (BSS), as a digital signal processing approach, focuses on estimating the underlying source signals from their linear...
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Traffic Parking Forecast of Traffic Area Based on Partial Least Squares Method
In order to predict the traffic parking demand in the city, a prediction model based on partial least squares method is proposed. With the...
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A Novel Least-Squares Polygonal Finite Element Level Set Method
In this study, we present a novel least-square polygonal finite element method to solve a hyperbolic level set (LS) convection-diffusion problem. In...
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An adaptive identification method for outliers in dam deformation monitoring data based on Bayesian model selection and least trimmed squares estimation
An important technique for the quantitative analysis of dam deformation state is to establish safety monitoring models using deformation monitoring...
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State Estimation in Electric Power Systems Using Weighted Least Squares Method
State estimation is a powerful method used in electric power systems, whose results are used for various purposes such as analysis, management and...
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Joint sparse least squares via generalized fused lasso penalty for identifying nonlinear dynamical systems
This paper proposes a joint sparse least-square model that utilizes a generalized fused lasso penalty to jointly identify governing equations of...
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Application of Weighted Least Squares Algorithm in Machine Vision System
The relationship between camera position and reconstruction accuracy is analyzed, and the weight value is estimated on this basis. The application of...
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A study on model calibration using sensitivity based least squares method
In the field of engineering, simulations are often used to save experimental cost and time. Since most of the simulation models have various model...
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On Weighted Least Squares Estimators of Parameters of a Chirp Model
The least squares method seems to be a natural choice in estimating the parameters of a chirp model. But the least squares estimators are very...
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Signal Frequency Estimation via Kalman Filter and Least Squares Approach for Non-uniform Signals
An innovative approach for estimating power system characteristics has been devised, and it is predicated on the Kalman filter (KF) and least squares...
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A New Partially-coupled Recursive Least Squares Algorithm for Multivariate Equation-error Systems
This paper focuses on the parameter estimation problems for multivariate pseudo-linear systems. Based on the parameters coupling characteristic of...