Results 161 to 170 of about 676,778 (198)

A weighted least squares method for first‐order hyperbolic systems

International Journal for Numerical Methods in Fluids, 1995
AbstractThe paper presents a generalization of the classical L2‐norm weighted least squares method for the numerical solution of a first‐order hyperbolic system. This alternative least squares method consists of the minimization of the weighted sum of the L2 residuals for each equation of the system. The order of accuracy of global conservation of each
Zeitoun, D. G., Laible, J. P., Pinder, G. F.   +2 more
openaire   +1 more source

Moving Weighted Least-Squares Methods

1979
Moving weighted least squares are defined and analyzed with a view to clarifying their algebraic structure and imposing sufficient conditions to guarantee interpolating and smoothness properties of the resulting surface.
openaire   +1 more source

Image denoising based on weighted regularized least square method

2017 International Conference on Circuit ,Power and Computing Technologies (ICCPCT), 2017
Noise in an image is caused due to various reasons. Removal of noise in an efficient way is a big challenge for researchers. In this paper, one dimensional signal denoising based on weighted regularized least square method is mapped to two dimensional image denoising.
M. Srikanth, K. S. Gokul Krishnan, V. Sowmya, K. P. Soman   +3 more
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Power System State Estimation using Weighted Least Square Method

Proceeding International Conference on Science and Engineering, 2023
State estimation is an essential part of every energy control management system. Accurate estimation of state or operating state is essential for security control and monitoring of power systems. Power system state estimation is a procedure to estimate true state from the inexact state of a power system.
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Weighted-beacon least square positioning method based on measurement

2010 Second International Conference on Ubiquitous and Future Networks (ICUFN), 2010
In this paper, we propose a simple location positioning method based on our own IR-UWB system. First, we examine the sampling characteristics of pulse-arrival-time. Second, we propose a simple location positioning method (WB-LS) based on our observation.
null Jimyung Kang, null Soonwoo Lee, null Moon-kyoung Kang, null Young-jin Park, null Kwanho Kim   +4 more
openaire   +1 more source

Least-Squares Delayed Weighted Gradient Method

Proceeding Series of the Brazilian Society of Computational and Applied Mathematics, 2022
Rafael Aleixo, Hugo Lara Urdaneta
openaire   +1 more source

Kernel and Local Weighted Least Squares Methods

1988
It is assumed from now on that in the model (2.1) $$ {\text{Y}}_i {\text{,n-g(t}}_{i,n} ) + \varepsilon _{i,n} {\text{ ,i = 1,}}...{\text{,n}} $$ where usually indices n are omitted, 0≤t1≤t2≤…≤tn≤l without loss of generality. As in (2.1), the errors are assumed to be i.i.d.
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Radiance Calibration Based on Weighted Least Square Method

Chinese Journal of Liquid Crystals and Displays, 2012
With the in-depth development of the infrared physics and infrared technology,the measurement of target radiation characteristics is widely appreciated.And the infrared detector radiometric calibration is a fundamental work.This paper establish a radiometric calibration system,the absolute radiometric calibration of the 3~5 μm infrared focal plane ...
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A least‐square weighted residual method for level set formulation

International Journal for Numerical Methods in Fluids, 2011
SUMMARYIn this paper, a least‐square weighted residual method (LSWRM) for level set (LS) formulation is introduced to achieve interface capturing in two‐dimensional (2D) and three‐dimensional (3D) problems. An LSWRM was adopted for two semi‐discretized advection and reinitialization equations of the LS formulation.
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Theory & Methods: Adaptive Estimation Using Weighted Least Squares

Australian & New Zealand Journal of Statistics, 2001
This paper proposes an adaptive estimator that is more precise than the ordinary least squares estimator if the distribution of random errors is skewed or has long tails. The adaptive estimates are computed using a weighted least squares approach with weights based on the lengths of the tails of the distribution of residuals.
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