Description: 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 for finding the
same for a set of Symmetric matrices.
[acdc_sym.m](note that for real-valued matrices the Hermitian and Symmetric cases are similar however, in such cases the Hermitian version
[acdc.m], rather than the Symmetric version[acdc_sym] is preferable.
* A function that finds an initial guess
for acdc by applying hard-whitening
followed by Cardoso s orthogonal joint
diagonalizer. Note that acdc may also
be called without an initial guess,
in which case the initial guess is set by default to the identity matrix.
The m-file includes the joint_diag
function (by Cardoso) for performing
the orthogonal part.
[init4acdc.m]
Platform: |
Size: 10609 |
Author:薛耀斌 |
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Description: 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 Platform: |
Size: 1648 |
Author:zt |
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Description: 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 Platform: |
Size: 1024 |
Author:zt |
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Description: 基于最小二乘原理的正交多项式拟PDF格式-Based on the principle of least squares orthogonal polynomials to PDF format Platform: |
Size: 67584 |
Author:高东飞 |
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Description: ％ 奇异值分解 (sigular value decomposition,SVD) 是另一种正交矩阵分解法；SVD是最可靠的分解法，
％ 但是它比QR 分解法要花上近十倍的计算时间。[U,S,V]=svd(A)，其中U和V代表二个相互正交矩阵，
％ 而S代表一对角矩阵。 和QR分解法相同者， 原矩阵A不必为正方矩阵。
％ 使用SVD分解法的用途是解最小平方误差法和数据压缩。用svd分解法解线性方程组，在Quke2中就用这个来计算图形信息，性能相当的好。在计算线性方程组时，一些不能分解的矩阵或者严重病态矩阵的线性方程都能很好的得到解- Singular value decomposition (sigular value decomposition, SVD) is another orthogonal matrix decomposition method SVD decomposition is the most reliable method, but it takes more than QR decomposition near ten times the computing time. [U, S, V] = svd (A), in which U and V on behalf of two mutually orthogonal matrix, and the S on behalf of a diagonal matrix. And QR decomposition are the same, the original matrix A is no need for the square matrix. The use of SVD decomposition method are used as a solution of least squares error method and data compression. Using SVD decomposition solution of linear equations, in Quke2 on to use this information to calculate the graphics performance quite good. In the calculation of linear equations, some indecomposable matrix or serious pathological matrix of linear equations can be a very good solution Platform: |
Size: 3072 |
Author:zhxj |
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Description: 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 function also returns in the vector ind the indexes of the
best r regressors (i.e., the best columns of A to use).
If r is equal to n, the solution x given by OLS is the same as the solution
given by A\b, but in ind we still have the regressors sorted by their
importance. This means that one can perform a feature selection by taking
the first k entries in ind (k<r). Platform: |
Size: 5120 |
Author:王詹 |
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Description: 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 Platform: |
Size: 1024 |
Author:kevin stone |
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Description: 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 Platform: |
Size: 1024 |
Author:王知行 |
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Description: 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 algorithm of fitting error is small. Platform: |
Size: 1024 |
Author:张科 |
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Description: 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 and so on. Platform: |
Size: 16384 |
Author:庞枫骞 |
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Description: 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 by Gradient Pursuit ols_nomp: Sparse reconstruction by Orthogonal Least Squares followed by Approximate Conjugate Gradient Pursuit ols_pcgp: Sparse reconstruction by Orthogonal Least Squares followed by Partial Conjugate Gradient Pursuit
The source code and files included in this project are listed in the project files section, please make sure whether the listed source code meet your needs there.
Platform: |
Size: 17408 |
Author:Virtyt |
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Description: 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 multidimensional case, an analytical solution may not exist (although Mr. Carr s function is an efficient approximation of the solution).-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 multidimensional case, an analytical solution may not exist (although Mr. Carr s function is an efficient approximation of the solution).
Platform: |
Size: 78848 |
Author:nanolilou |
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Description: 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.) Platform: |
Size: 1024 |
Author:liyuqi920105 |
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Description: 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.) Platform: |
Size: 1024 |
Author:liyuqi920105 |
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Description: 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 by Gradient Pursuit ols_nomp: Sparse reconstruction by Orthogonal Least Squares followed by Approximate Conjugate Gradient Pursuit ols_pcgp: Sparse reconstruction by Orthogonal Least Squares followed by Partial Conjugate Gradient Pursuit
The source code and files included in this project are listed in the project files section, please make sure whether the listed source code meet your needs there. Platform: |
Size: 16384 |
Author:choesongil |
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Search - orthogonal least squares