Results 31 to 40 of about 12,450 (173)
A parametric framework for multidimensional linear measurement error regression
PLoS ONE, 2022 The ordinary linear regression method is limited to bivariate data because it is based on the Cartesian representation y = f(x). Using the chain rule, we transform the method to the parametric representation (x(t), y(t)) and obtain a linear regression ...
Stanley Luck
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A general iterative solver for unbalanced inconsistent transportation problems [PDF]
Archives of Transport, 2016 The transportation problem, as a particular case of a linear programme, has probably the highest relative frequency with which appears in applications. At least in its classical formulation, it involves demands and supplies.
Doina Carp +2 more
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Design and Implementation of a Machine Learning State Estimation Model for Unobservable Microgrids
IEEE Access, 2022 An observable microgrid may become unobservable when sensors are at fault, sensor data is missing, or data has been tampered by malicious agents.
Byron Alejandro Acuna Acurio +4 more
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Kernel and Range Approach to Analytic Network Learning
International Journal of Networked and Distributed Computing (IJNDC), 2018 A novel learning approach for a composite function that can be written in the form of a matrix system of linear equations is introduced in this paper.
Kar-Ann Toh
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Weaker assumptions for convergence of extended block Kaczmarz and Jacobi projection algorithms
Analele Stiintifice ale Universitatii Ovidius Constanta: Seria Matematica, 2017 Recent developments in the field of image reconstruction have given rise to the use of projective iterative methods, such as Kaczmarz and Jacobi, when solving inconsistent linear least squares problems. In this paper we try to generalize previous results
Carp Doina +2 more
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Journal of Applied Mathematics, 2003 A comprehensive treatment of Rayleigh-Schrödinger perturbation theory for the symmetric matrix eigenvalue problem is furnished with emphasis on the degenerate problem. The treatment is simply based upon the Moore-Penrose pseudoinverse thus distinguishing
Brian J. McCartin
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Российский технологический журнал, 2022 Objectives. Recent research in machine learning and artificial intelligence aimed at improving prediction accuracy and reducing computational complexity resulted in a novel neural network architecture referred to as an extreme learning machine (ELM).
L. A. Demidova, A. V. Gorchakov
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Error propagation in polarimetric demodulation [PDF]
, 2008 The polarization analysis of the light is typically carried out using modulation schemes. The light of unknown polarization state is passed through a set of known modulation optics and a detector is used to measure the total intensity passing the system.
Collados, M., Ramos, A. Asensio
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An assessment of the performance of a 1.5 μm Doppler lidar for operational vertical wind profiling based on a 1-year trial [PDF]
Atmospheric Measurement Techniques, 2015 We present the results of a 1-year quasi-operational testing of the 1.5 μm StreamLine Doppler lidar developed by Halo Photonics from 2 October 2012 to 2 October 2013.
E. Päschke, R. Leinweber, V. Lehmann
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Inference in the indeterminate parameters problem
Statistica, 2013 We face an indeterminate parameters problem when there are two sets of parameters, x and g, say, such that the null hypothesis H0:x=x0 makes the likelihood independent of g. A consequence of indeterminacy is the singularity of the information matrix. For
Marco Barnabani
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