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this directory
contains the following:
* The acdc algorithm for finding the
approximate general (non-orthogonal)
joint diagonalizer (in the direct Least Squares sense) of a set of Hermitian matrices.
[acdc.m]
* The acdc algorithm
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基于最小二乘原理的正交多项式拟和输入原始数据及拟和次数即可输出最终拟和表达式系数-based on the principle of least squares orthogonal polynomials and to the importation of the raw data and can be exported and the number of proposed and final expression coefficient
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基于非等距节点的正交多项式的最小二乘法拟合算法之程序实现-Nodes based on non-isometric orthogonal polynomial least squares fitting algorithm of the program
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最小二乘问题的解法
最小二乘问题
正则化算法
正交变换
正交化算法-Least-squares problem Least Squares Solution of the problem is the orthogonal transform algorithm of the orthogonal algorithm
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MATLAB程序，
半参数线性回归模型的最小二乘核估计
半参数线性回归模型的最小二乘正交序列估计。-MATLAB program, semi-parametric linear regression model of least squares kernel estimation Semiparametric least squares linear regression model orthogonal sequence estimation.
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该算法是用正交多项式来求最小二乘拟合多项式。-This algorithm is to use orthogonal polynomials to seek least-squares polynomial fitting.
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正交最小二乘辨识算法
该算法除了实现最小二乘辨识功能之外而且能按照各项重要性将其逐一选出并且估计相应系数-OLS Orthogonal Least Quares.
[x, ind] = OLS(A,b,r) gives the solution to the least squares problem
using only the best r regressors chosen from the ones present in matrix A.
This
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给定一组数据 进行最小二乘拟合 包括使用以正交多项式为基底的拟合-Given a set of data, including the use of orthogonal least squares polynomial fitting for the basement
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通过正交点的寻找从而用几何最小二乘拟合椭圆的方法-Finding points to the orthogonal least squares fitting using the geometric method of elliptic
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本程序是基于非等距节点的正交多项式的最小二乘法拟合算法，该算法已经在vc++6.0下调试通过，经多次验证，本算法的拟合误差较小。-This procedure is based on equidistant nodes of non-orthogonal polynomial least squares fit algorithm, which has been in vc++6.0 through debugging, after repeated verification, the algo
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正交多项式最小二乘曲线拟合c语言程序代码-Orthogonal polynomial least squares curve fitting
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基于稀疏表示的正交最小二乘法，使用的语言是matlab，应用比较广阔，设计信号处理中的信号回归，图像处理的压缩等。-Sparse representation based on orthogonal least squares method, the language used is matlab, relatively broad application, design signal processing signal return, image processing, compression
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基于正交最小二乘算法的RBF网络设计，精简RBF网络结构！-Based on the orthogonal least squares algorithm of RBF network design, streamline RBF network structure
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The following Matlab project contains the source code and Matlab examples used for orthogonal least squares algorithms for sparse signal reconstruction. Added after previous version ols_gp: Sparse reconstruction by Orthogonal Least Squares followed b
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Orthogonal Least Squares Estimate on a plane, in the simple case of a linear equation, is in fact a problem that can be easily solved analytically with no approximation (see pdf file for detailed explanation). Notice that in the general multidimensio
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Analytical solution for Orthogonal Linear Least Squares in two dimensions
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orthogonal least squares algorithms for sparse signal in MATLAB.
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matlab正交最小二乘法源程序，可实现矩阵元素的正交最小二乘拟合，确定系数值等(Matlab orthogonal least square source program, can realize the matrix element orthogonal least squares fitting, determination coefficient value, and so on.)
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matlab施密特正交化源程序，可结合矩阵元素的正交最小二乘拟合，确定系数值等(Matlab schmidt orthogonalization source program, can combine matrix element orthogonal least squares fitting, determination coefficient value and so on.)
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The following Matlab project contains the source code and Matlab examples used for orthogonal least squares algorithms for sparse signal reconstruction. Added after previous version ols_gp: Sparse reconstruction by Orthogonal Least Squares followed b
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