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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-Penalized Poisson Likelihood E
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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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regularization solver by Tikhonov method
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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 comparison between the four algorith
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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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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
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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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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
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正则化去除噪声,效果撮合,凑合。。。。。。(Tikhonov regularization)
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tikhonov求解,正则化参数为0.1,应用svd分解,求解病态矩阵的解。(Tikhonov solution, regularization parameter is 0.1, using SVD decomposition to solve the ill-conditioned matrix solution.)
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