And then, according to different types of quadric surface, using the geometric parameter equation, the technology of extracting quadric surface can be achieved based on least square method. The results of the study show that: For normal data or less noisy data, the accuracy of calculation of ...
A new approach in regression analysis for modeling adsorption isotherms For the calculation of the constants [C.sub.11], [C.sub.12], [C.sub.21], [C.sub.22], and [C.sub.31] using (33) in (19) and applying the method of least square mentioned in (16)-(17) by taking, we get...
The Least Mean Square (LMS) solution is a method that provides the integration of all equations in a unique solution finding the solution where the addition of all errors is minimum [6]. From: Alexandria Engineering Journal, 2011 About this pageSet alert Discover other topics On this page Def...
For linear problems, this will mean that m = n and that the design matrix X is square. If X is nonsingular, the β's are the solution to a square system of linear equations: β = X \y. • Least squares: Minimize the sum of the squares of the residuals: ∑m ∥r∥2 = ri2...
Projection Method for Eigenvalue Problems of Linear Nonsquare Matrix Pencils The primary cost lies in the solutions of linear least squares problems that arise from quadrature points, and they can be readily parallelized in practice... K Morikuni - Society for Industrial and Applied Mathematics 被...
In this work, we develop a distributed least squares approximation (DLSA) method that is able to solve a large family of regression problems (e.g., linear regression, logistic regression, and Cox's model) on a distributed system. By approximating the local objective function using a local q...
Application of Three-Dimensional Direct Least Square Method for Ellipsoid Anisotropy Fitting Model of Highly Irregular Drill Hole Patterns Ellipsoid or geometric anisotropy is a widely used method in geostatistical analysis to obtain variograms with different ranges in different directions (az... I Much...
213), where r=vb(R) and vb(·) denotes the vectorizing operator taking the elements below the main diagonals of a square matrix, though the method is not dealt with in this article. Using the r×1 Lagrange multiplier vector ξρ as before with the q∗×1 vector ηρ=(θρ′,ξ...
It approximates the manifold structure and differential operators based on moving least square approximation parametrized by the tangent space locally. The other one is called the local mesh method which mimics the finite element method. By generating a local mesh for a point cloud through its ...
3) mi nimal least square method 极小最小二乘法4) LSQR 最小二乘QR分解算法 1. LSQR and ART algorithms are applied separately to calculate tomography for the determined system of equation,overdetermined system of equation and underdetermined system of equation. 采用弯曲射线追踪算法计算走时,分别...