nonlinear least-squares
Solving Nonlinear Least Squares Problem Using Gauss-Newton Method
... The iterative algorithm of the Gauss-Newton method that is used for solving the nonlinear least squares problem was discussed in this paper. In general, it is typically difficult to decide an ...
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Nonlinear Least Squares Estimation of the Shifted Gompertz Distribution
... by nonlinear least squares fitting the adoption ...c. Nonlinear weighted least squares estimation of a three-parameter Weibull density with a nonparametric ...
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Newton Krylov Type Algorithm for Solving Nonlinear Least Squares Problems
... The minimization of a quadratic function within an ellipsoidal trust region is an important subproblem for many nonlinear programming algorithms. When the number of variables is large, one of the most widely used ...
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Solution of the Nonlinear Least Squares problem using a new Gradient Based Genetic Algorithm
... In this paper a novel Gradient based Genetic Algorithm (GDGA) that synergistically combines the global random search ability of the genetic algorithm and computationally efficient local search ability of the Nelder-Mead ...
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NLINLS: a Differential Evolution based nonlinear least squares Fortran 77 program
... Introduction: Curve fitting or estimation by nonlinear least squares is a difficult task. There are two types of algorithm that are often used for this purpose: those that need evaluation of ...
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Estimation of the internal shear strength distribution of the element for laminated veneer lumber by nonlinear least-squares method
... 3. Komatsu K (1997) Prediction of maximum bending moment of glulam beam composed of arbitrary laminae and verification by experiment results (in Japanese). Mokuzai Gakkaishi 43:934–939 4. Koseki M, Nakamura N (2012) ...
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Estimation and inference in unstable nonlinear least squares models
... to nonlinear models. To that end, we consider a nonlinear model that can be estimated via nonlinear least squares (NLS) and features a limited number of parameter shifts occur- ring at ...
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Estimation and Inference in Unstable Nonlinear Least Squares Models (Final)
... cumulative sum (CUSUM) and CUSUM-of-squares tests. This test is generalized to dynamic models by Kr¨amer, Ploberger, and Alt (1988). The CUSUM of squares test based on recursive residuals was shown to ...
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Performance of Differential Evolution Method in Least Squares Fitting of Some Typical Nonlinear Curves
... IV. The Findings: In what follows, we present our findings on the performance of the Differential Evolution method at optimization of the Least Squares problems. The datasets and the models are available at ...
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On determination of cointegration ranks
... ordinary least squares (Engle and Granger (1987)), nonlinear least squares (Stock (1987)), maximum likelihood in an error correction model (Johansen (1988)), principal components (Stock ...
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Consistent least squares fitting of ellipsoids
... The OLS estimation of the ellipsoid parameters from noisy measurements of points on its boundary is a nonlinear least squares problem. An indirect, suboptimal approach was used that transforms the ...
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Object Detection and Tracking Using Uncalibrated Cameras
... In chapter 8, the experimental results on simulated data to evaluate the performance of camera calibration algorithm and the object tracking algorithm are presented. Synthetic data for an object is generated assuming the ...
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Hybrid Levenberg–Marquardt and weak-constraint ensemble Kalman smoother method
... weighted nonlinear least-squares ...the squares of the differences of the initial state from a known background state at the initial time and the differences of the values of the observation ...
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On weighted structured total least squares
... The equivalent optimization problem (1) is a nonlinear least squares prob- lem, so that classical optimization methods can be used for its solution. The optimization methods require a cost function ...
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Image magnification by least squares surfaces
... In recent years, nonlinear interpolation methods have been used to reform linear methods for improving image quality and solving the blur problem. The change of non-linear methods depends on the interpolation ...
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Overview of total least squares methods
... total least squares ...total least squares approach for spectral estimation with extensions to decimation and multichannel data quantification [35, ...the least mean squares ...
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Deformation analysis with Total Least Squares
... tion using generalized eigensystem analysis, in: Statistical Meth- ods in Video Processing, edited by: Comaniciu, D., Kanatani, K.-I., Mester, R., Suter, D., ECCV 2004 Workshop SMVP 2004, Prague, Czech Republic, 16 May ...
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A novel interpretation of least squares solution
... We show that the well-known least squares LS solution of an overdetermined system of linear equations is a convex combination of all the non-trivial solutions weighed by the squares of t[r] ...
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Teaching Least Squares in Matrix Notation
... generalized least squares can be thought at the second year undergraduate with reasonable appreciation from the ...the least squares allows to easily retrieve the results obtainable with ...
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