Least-Squares Problem
The element wise weighted total least squares problem
... total least-squares method yields an inconsistent estimate of the parameter in this ...total least-squares problem, called element-wise weighted total least-squares, is ...
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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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Current identification in vacuum circuit breakers as a least squares problem*
... inverse problem needs to be solved, allowing the determination of the causes, ...inverse problem to solve for the current reconstruction in the circuit breaker ...the least squares solution of ...
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Updating QR factorization procedure for solution of linear least squares problem with equality constraints
... linear least squares problem with equality ...constrained problem to unconstrained linear least squares and partition it into a small ...
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Solution of the Nonlinear Least Squares problem using a new Gradient Based Genetic Algorithm
... nonlinear least squares method for material characterization using elastic waves" [8] make use of a material characterization problem in which parameters are determined by minimizing error ...
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On weighted structured total least squares
... Abstract. In this contribution we extend our previous results on the structured total least squares problem to the case of weighted cost func- tions. It is shown that the computational complexity of ...
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On the computation of the structured total least squares estimator
... constrained least squares problem is ...constrained least squares problem is eciently solved via the Generalized Schur ...STLS problem have computational cost linear in m ...
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Overview of total least squares methods
... total least squares method and describe algorithms for its generalization to weighted and structured approximation ...total least squares problem has a unique solution, which is given ...
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Off -Grid Direction-of-Arrival Estimation Using a Sparse Array Covariance Matrix
... Abstract—An off-grid direction-of-arrival (DOA) estimation method that utilizes a sparse array covariance matrix is proposed. In this method, the array covariance matrix is sparsely represented in the form of a vector and ...
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05_Linear_Regression_1.pdf
... Maximum Likelihood and Least Squares Geometry of Least Squares Sequential Learning Regularized Least Squares Multiple Outputs Loss Function for Regression The Bias-Variance Decomposition[r] ...
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Image magnification by least squares surfaces
... This paper continues as follows. In the second part, quadratic surfaces and the theory of least squares will be discussed. In the third part, the least square planes, suggested algorithms, and ...
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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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Least squares approximations of power series
... classical least squares solutions in C[ − 1, 1] in terms of linear combinations of ul- traspherical polynomials are extended in order to estimate power series on ( − 1, ...
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Distributed Learning with Regularized Least Squares
... produces distributed learning algorithms consisting of three steps: partitioning the data into disjoint subsets, applying a particular learning algorithm implemented in an individual machine to each data subset to ...
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Some aspects of progeny testing Southdown rams : a thesis presented in part fulfilment of the requirements for the degree of Master of Agricultural Science in Massey University of Manawatu, New Zealand
... Least squares means, least squares deviations of sire groups from the means, least squares differences due to birthrank and sex, and partial regression coefficients for the characteristi[r] ...
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Optimal Dictionary for Least Squares Representation
... of problem (7) is bounded be- low by the optimal value, if it exists, of the one given in ...optimization problem (21) admits a solution, and we shall furnish a feasible solution of (7) that achieves a ...
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Teaching Least Squares in Matrix Notation
... The least squares method, a fundamental piece of knowledge for students of all scientific tracks, is often introduced considering the simple linear regression with only two parameters to be ...the ...
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RLScore: Regularized Least-Squares Learners
... RLScore scales to orders of magnitude larger problem sizes than the baselines on all but the LOO experiment. With the exception of LOO, none of the considered fast algorithms are available in other software ...
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ONLINE NON-NEGATIVE MATRIX FACTORIZATION FOR CLUSTERING OF NEWS DOCUMENT
... The product is called a nonnegative matrix factorization of V. It is not possible to find a unique solution to the above problem as the function is non-convex in terms of W and H. Also, we can prove that is ...
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Least Squares Solution for Discrete Time Nonlinear Stochastic Optimal Control Problem with Model Reality Differences
... the real-world problems. The behavior of the fluctuation, which is caused by the effect of noise disturbance in the dynamical system to represent the real situa- tion, rises to the attention of many researchers. See for ...
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