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ere we provide codes for a very powerful Lanczos based hybrid
iterative method that can be used for large scale linear ill-posed
inverse problems. The method will automatically choose [Tikhonov]
regularization parameters, and automatically determ
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利用Tikhonov正则化实现的超分辨率图像序列的重建，效果还好-Use Tikhonov regularization to achieve super-resolution image sequence reconstruction, better results
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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
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Tikhonov正则化的很有用的MATLAB程序-Tikhonov regularization useful MATLAB program
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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
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论文Tikhonov, Ivanov and Morozov regularization for support vector machine learning(paper, Tikhonov, Ivanov and Morozov regularization for support vector machine learning)
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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
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