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Tikhonov_regularization_toolbox
- Tikhonov正则化工具箱，可实现病态方程组的正则化，以及采用L曲线法、岭估计法、GCV法等确定正则化参数，内含使用方法，亲测有效。-Tikhonov regularization toolbox, which can realize regularization in morbid equations, and using the L curve method, ridge estimation, GCV method to determine the regularization para
gongetidufa
- 一种共轭梯度法的matlab函数，可以用于求解病态的线性方程组，提高求解精度.还提供了算法的介绍文档-A conjugate gradient method of matlab function, can be used to solve ill-conditioned linear equations, improve the accuracy of solving
tikhonov
- 该算法用于求解线性病态逆问题，同时该算法已经过实际验证，重建结果较好，希望对大家有所参考。-The algorithm for solving linear pathological inverse problem, at the same time, the algorithm was validated through actual and reconstruction results are good, hope to be of reference.
OVM
- A Dynamical Tikhonov Regularization for Solving Ill-posed Linear Algebraic Systems.pdf，以上论文提出的求解病态线性方程组的一种较新梯度下降法-A Dynamical Tikhonov Regularization for Solving Ill-posed Linear Algebraic Systems.pdf, more than one paper proposes solving ill-conditi
tikhonov
- 计算病态反问题时所采用的的正则化方法(Regularization method used in the computation of ill posed inverse problems)
csvd+ttls
- ttls的正则化方法，适用于各种病态反问题的求解(The regularization method of ttls is applicable to solving various ill conditioned inverse problems)
tgsvd+tsvd
- tgsvd正则化方法，适用于计算各类病态反问题(The tgsvd regularization method is suitable for the calculation of ill posed inverse problems)
ILP
- 病态线性方程组的一些求解算法，包括传统的CG，CGLS，CGNR，LSQR和较新的OVM算法，它们都是一些迭代算法。(Some solving algorithms for ill conditioned linear equations include conventional CG, CGLS, CGNR, LSQR, and newer OVM algorithms, all of which are iterative algorithms.)
最小二乘曲面拟合
- 基于最小二乘的曲面拟合算法，该算法考虑了法方程的病态性，利用雅各比迭代法有效求解方程。(Based on the least squares surface fitting algorithm, the algorithm takes into account the ill conditioning of the normal equation, and uses Jacoby iterative method to solve the equation effectively.)
ridge regression1
- 岭回归(英文名：ridge regression, Tikhonov regularization)是一种专用于共线性数据分析的有偏估计回归方法，实质上是一种改良的最小二乘估计法，通过放弃最小二乘法的无偏性，以损失部分信息、降低精度为代价获得回归系数更为符合实际、更可靠的回归方法，对病态数据的拟合要强于最小二乘法。 总之，本文档是岭回归的R语言实现代码，主要用于解决当模型中出现多重共线性问题，尤其是当你所有的解释变量都很重要，又无法通过其他检验来删除时，岭回归是一个很好的解决办法。(Ridge
tikhonov
- 解病态方程的正则化方法、逆问题不适定解的处理与正则化(Regularization method for solving ill conditioned equations)
L曲线法
- 用MATLAB编写的病态方程的L曲线解决方法，可以通过L曲线确定所需的参数。(MATLAB prepared by the ill conditioned L curve solution, you can determine the required parameters through the L curve.)
Regularization Tools Version 4.1
- matlab 正则化工具包 可以下载解压后在matlab中直接使用，解决病态方程的计算问题(Matlab regularization Toolkit)
ill-conditioned system of equations
- 分别用几种经典的数值分析迭代算法求解线性方程组(Solving linear equations by several classical numerical analysis iterative algorithms)
线性方程组计算
- 利用高斯消元法法求解病态矩阵——hilbert 矩阵的线性方程组。通过条件数分析，找出误差较大的原因。再利用 Jacobi 迭代方法、G-S 迭代方法和 SOR 迭代法做了进一步探究。另外，作为要求之外的，还使用共轭梯度法来求解方程以来进行对比，并利用Tikhonov 正则化的方法改善矩阵的条件数，来减小误差。(The Gauss elimination method is used to solve the linear equations of the ill conditioned mat
JavaNotepad-master
- 大部份的优化问题都是多峰函数或病态函数，为了克服基本粒子群算法的缺陷，我研究了以下四种改进的粒子群算法(Most optimization problems are multi-peak functions or ill-conditioned functions. In order to overcome the defects of basic particle swarm optimization, I studied the following four improved particl
Matlab-RegularizationTools
- Matlab程序包解决病态的正则化反演问题(A Matlab Package for Analysis and Solution of Discrete Ill-Posed Problems)
正则化方法
- 在进行矩阵求逆等计算时遇到矩阵条件数较大导致病态时，常用的各种解决病态方程方法(In the calculation of matrix inversion, when the number of matrix conditions is large, which leads to ill condition, various common methods to solve ill condition equation are used)