Results 21 to 30 of about 419,205 (270)

An Iterative Method Based on the Marginalized Particle Filter for Nonlinear B-Spline Data Approximation and Trajectory Optimization

Mathematics, 2019
The B-spline function representation is commonly used for data approximation and trajectory definition, but filter-based methods for nonlinear weighted least squares (NWLS) approximation are restricted to a bounded definition range.
Jens Jauch, Felix Bleimund, Michael Frey, Frank Gauterin   +3 more
doaj   +1 more source

Function Synthesis of the Planar 5R Mechanism Using Least Squares Approximation [PDF]

, 2014
In this paper, the problem of function generation synthesis of planar 5R mechanism is studied using the least squares approximation method with equal spacing of the design points. The study represents a case study for analytical function generation of multi-degrees-of-freedom systems.
Kiper, Gökhan, Bağdadioğlu, Barış, Bilgincan, Tunç   +2 more
openaire   +1 more source

Interpretation and Semiparametric Efficiency in Quantile Regression under Misspecification

Econometrics, 2015
Allowing for misspecification in the linear conditional quantile function, this paper provides a new interpretation and the semiparametric efficiency bound for the quantile regression parameter β (
Ying-Ying Lee
doaj   +1 more source

Simulation of the of the DeepLabv3 neural network learning process for the agricultural fields segmentation

Вестник Дагестанского государственного технического университета: Технические науки, 2023
Objective. Monitoring and determining the state of crops in agricultural production requires the use and improvement of neural network methods of artificial intelligence.The aim of the study is to create a mathematical model of the learning process of ...
A. F. Rogachev, I. S. Belousov
doaj   +1 more source

Quadrature-Based Vector Fitting: Implications For H2 System Approximation

, 2014
Vector Fitting is a popular method of constructing rational approximants designed to fit given frequency response measurements. The original method, which we refer to as VF, is based on a least-squares fit to the measurements by a rational function ...
Beattie, Christopher, Drmac, Zlatko, Gugercin, Serkan   +2 more
core   +1 more source

A frequentist analysis of solar neutrino data [PDF]

, 2000
We calculate with Monte Carlo the goodness of fit and the confidence level of the standard allowed regions for the neutrino oscillation parameters obtained from the fit of solar neutrino data.
Abdurashitov, Akhmedov, Bahcall, Bahcall, Bilenky, Bilenky, C. Giunti, Caso, Chizhov, Chizhov, Cleveland, Cousins, de Gouvea, Eadie, Feldman, Fogli, Fogli, Fogli, Fogli, Fogli, Fogli, Friedland, Frodesen, Garzelli, Giunti, Giunti, Gonzalez-Garcia, Gonzalez-Garcia, Hampel, Kirsten, Krastev, Krastev, Krastev, Kuo, Liu, M.V. Garzelli, Mikheyev, Parke, Petcov, Petcov, Press, von Feilitzsch, Wolfenstein, Wolfenstein   +43 more
core   +3 more sources

COMPARATIVE ANALYSIS OF ESTIMATION METHODS FOR CES PRODUCTION FUNCTION [PDF]

Annals of the University of Petrosani: Economics, 2015
This article describes the analysis of the stationary and dynamic case of the Kmenta method for estimating the CES production function. The data series which occur in the analysed models, are given by the real gross value added, regarded as output ...
NADIA ELENA STOICUŢA, OLIMPIU STOICUŢA
doaj  

Least-Squares Solutions of the Matrix Equations AXB+CYD=H and AXB+CXD=H for Symmetric Arrowhead Matrices and Associated Approximation Problems

Journal of Applied Mathematics, 2014
The least-squares solutions of the matrix equations AXB+CYD=H and AXB+CXD=H for symmetric arrowhead matrices are discussed. By using the Kronecker product and stretching function of matrices, the explicit representations of the general solution are given.
Yongxin Yuan
doaj   +1 more source

An Adaptive Policy Evaluation Network Based on Recursive Least Squares Temporal Difference With Gradient Correction

IEEE Access, 2018
Reinforcement learning (RL) is an important machine learning paradigm that can be used for learning from the data obtained by the human-computer interface and the interaction in human-centered smart systems. One of the essential problems in RL algorithms
Dazi Li, Yuting Wang, Tianheng Song, Qibing Jin   +3 more
doaj   +1 more source

Identification of Nonlinear State-Space Systems via Sparse Bayesian and Stein Approximation Approach

Mathematics, 2022
This paper is concerned with the parameter estimation of non-linear discrete-time systems from noisy state measurements in the state-space form. A novel sparse Bayesian convex optimisation algorithm is proposed for the parameter estimation and prediction.
Limin Zhang, Junpeng Li, Wenting Zhang, Junzi Yang   +3 more
doaj   +1 more source