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svm-km
- 支持向量机(SVM)是数据挖掘中的一个新方法,能非常成功地处理回归问题(时间序列分析)和模式识别(分类问题、判别分析)等诸多问题,并可推广于预测和综合评价等领域,因此可应用于理科、工科和管理等多种学科。目前国际上支持向量机在理论研究和实际应用两方面都正处于飞速发展阶段。它广泛的应用于统计分类以及回归分析中. 支持向量机属于一般化线性分类器.他们也可以认为是提克洛夫规则化(Tikhonov Regularization)方法的一个特例.这
regularsolution
- 这是关于数学物理不适定问题正则化解算法的Matlab源程序-This is on the ill-posed problems of mathematical physics is the source Matlab algorithm to resolve
NonnegJune2009
- 当前论文主要考虑的是非信号依赖的高斯噪声下的图像恢复,本程序实现了泊松噪声下的图像恢复,泊松噪声为信号依赖噪声,能够更加有效逼近实际成像系统噪声。- This is the code that was used in the papers "A Nonnnegatively Constrained Convex Programming Method for Image Reconstruction", "Total Variation-
tlv
- 一篇关于tv和tikhonov模型处理图像的算法-An article on TV and tikhonov model of the image processing algorithm
Regularization-Method
- 正则化方法包括Tikhonov,tsvd,ttls,tgsvd,csvd-Regularization Method include Tikhonov,tsvd,ttls,tgsvd,csvd.
MAP-Tikhonov
- 基于正则化项的最大后验概率重建的一段程序,简单易懂-Based on regularization item maximum a posteriori probability reconstruction of a program, simple and understandable
111
- 走时层析成像的迭代Tikhonov正则化反演研究 走时层析成像的迭代Tikhonov正则化反演研究-Go tomography by iterative Tikhonov regularization inversion study of travel time tomography by iterative Tikhonov regularization inversion of
conv1D_04_Tikhonov
- Tikhonov正则化的很有用的MATLAB程序-Tikhonov regularization useful MATLAB program
solver
- regularization solver by Tikhonov method
reconstruction_algorithms
- 本代码主要给出了激光粒度仪颗粒散射光强分布以及4种粒度反演算法,以及4种算法之间的比较。四种反演算法为:TSVD、Chaine、Tikhonov和l1正则化。-The code gives the Zetasizer particle scattering intensity distribution, and four kinds of particle inversion algorithm, as well as a compar
super-resolution-Regularization-
- 本程序包括了三个程序,L1范数正则化,L2范数正则化,Tikhonov正则化超分辨率重建。经反复测试,没有BUG。-The program includes three procedures, L1 norm regularization, L2 norm regularization, Tikhonov regularization super-resolution reconstruction. After repeated tes
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 det
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
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 pape
Tikhonov-
- 基于变分方法 灰度图像 去噪 第一个简单模型 处理效果较好-A simple model based on variational method for image denoising is better
Sparsity_SDOCT_Software_2012
- Main.m: the file to run the software Instructions how to use the GUI_interface Step 1: click the 'open test' button to input the test noisy image and click the 'open averaged'button to input the averaged image Step 2:
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
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 equati