linear least-squares approach
Closed form Inverse Determination of Force Excitations for Undamped and Damped Linear systems Using a Least squares Approach
... While inverse approaches for unknown force excitations or system properties have also been considered for vibration problems in the past, they have had limitations or been numerically based. Briefly, Dobson and Rider [3] ...
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A Derivative-free Algorithm for Finding Least Squares Solutions of Quasi-linear and Linear Systems
... Quasi-linear solver presented in the paper is computationally one of the simplest algorithms for solving systems of quasi-linear equations ap- plying optimization approach but, at the same time, it ...
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Least Squares Solutions of Inconsistent Fuzzy Linear Matrix Equations
... fuzzy linear matrix equations (shown as IFLME) of the form AXB = C for finding its fuzzy least squares solutions is studied in this ...embedding approach, we extend it into a 2me × 2nr crisp ...
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Fuzzy Least Squares Linear Regression Approach to Ascertain Stochastic Demand in the Vehicle Routing Problem
... the linear combination of the dependent variables generates inde- pendent ...Fuzzy least squares liner regression is a powerful tool for decision making in fuzzy environ- ...
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A Simulation-based Portfolio Optimization Approach with Least Squares Learning
... One can see from the figures of Table V, the calibration phase for 5000 simulated sample paths took more than four hours to finish. The computation time also depends on the size of the strategy set and the number of the ...
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A Constrained Least Squares Approach to Mobile Positioning: Algorithms and Optimality
... of linear equations by introducing an intermediate variable, which is a function of the source position, and this technique is com- monly called spherical interpolation (SI) ...the linear equations via ...
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The Equivalence of the Maximum Likelihood and a Modified Least Squares for a Case of Generalized Linear Model
... likelihood approach is applied when the data are approximately ...second approach that we will consider is applied for normal or not normal data, but it is often applied for the second ...generalized ...
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Source term estimation of pollution from an instantaneous point source
... The approach taken was to develop the inverse model as a non-linear least squares estimation problem in which the source term was estimated using pollution concentration measurements on [r] ...
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The Additional Dynamics of the Least Squares Completions of Linear Differential Algebraic Equations
... Completing a DAE to an ODE has been a major approach for numerically solving DAEs for twenty years. This is especially advantageous for unstructured higher index systems since the direct application of numerical ...
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01_chap02_StatisticalLearning.pdf
... The most common approach for estimating the parameters in a linear model is ordinary least squares (OLS). However, this is only one way[r] ...
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The Dual of the Least Squares Method
... the least-squares estimates of a linear system’s parameters were thought to have been discovered, there surfaced an intriguing question: What is the dual specification of the ...
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Characterising the Human Auditory System using a Linear Least Squares System Identification Approach
... novel approach for objectively determining hearing thresholds using TRF estimation and ...this approach, our analyses did seem to indicate that there is a relationship between reconstruction accuracy and ...
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A Least-squares Approach to Direct Importance Estimation
... LSIF is shown to be efficient in computation, but it tends to share a common weakness of reg- ularization path tracking algorithms, that is, accumulation of numerical errors (Scheinberg, 2006). The numerical problem ...
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Hybrid Levenberg–Marquardt and weak-constraint ensemble Kalman smoother method
... a linear least-squares solver in ...ensemble approach is naturally parallel over the ensemble ...dense linear algebra li- braries can be used; however, in high-dimensional systems or ...
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Predicting the quality of ryegrass using hyperspectral imaging
... This study examines the utility of Hyperspectral Imag- ing (HSI) based methods for non-invasive assessment of the composition of ryegrass. The quality of forage is an important component of animal performance and envi- ...
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Partial Least Squares in Constructing Candidates Model Averaging Muhammad Arna Ramadhan, Bagus Sartono, Anang Kurnia
... We showed plots of actual value of the response variable and prediction in Figure 2. Both of methods, RMA and CMA yielded random pattern, while PLSMA yielded linear pattern. This pattern showed that PLSMA produced ...
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Least squares estimation of a shift in linear processes
... the least squares method (LS) to the estimation of a shift ...The least squares procedure also allows a broader specification of correlation structure in the data than MLE can typically ...a ...
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An Algorithm for Non Linear Data Fit by the Least Squares Method EUR 4959
... 16/11/49 DATE 72353 FORTRAN IV G LEVEL MINIMI SUBROUTINE MINIMI FUN,FM,X,G,H,N,M,IRIT,EPSF,EPSX,EPSG,I MAX,NIT, MINI 0001 liNVERT mm C MINI c MINI .MINI c MINI PROGRAM CALCULATES MINIMUM[r] ...
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On the Equivalence of the Weighted Least Squares and the Generalised Least Squares Estimators, with Applications to Kernel Smoothing
... the linear system (20) is redundant: the last h rows of the complete matrix [ K |i] can be deleted thus giving rise to a system of h + 1 equations in 2h + 1 unknown variables, let us denote it by K † σ = i † , ...
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Approximate Least Squares Accelerator
... Truncation of partial products is normally done by removing AND gates (Fig. 12). If this approach is used here, however, it will lead to a slightly different architecture compared to the recursive multipli- ers. ...
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