学习稀疏编码day2-Pursuit Algorithms – Practice

最新推荐文章于 2018-04-09 15:09:59 发布
最新推荐文章于 2018-04-09 15:09:59 发布
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分类专栏： 机器学习 文章标签： sparsecoding
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本文链接：https://blog.youkuaiyun.com/smilebluesky/article/details/40323705
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本文为《Sparse and Redundant Representations》第三章笔记，详细介绍了求解稀疏编码X的几种算法，包括正交匹配追赶(OMP)、LS_OMP、MP、weak_MP和阈值算法。重点解析了OMP算法的步骤，它通过寻找最小误差项来逐步构建支持域，并利用最小二乘法更新解，直至满足迭代次数或残差阈值。

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本篇文章是我看《Sparse and Redundant Representations-From Theory to Applications in Signal and Image Processing》书的第三章Pursuit Algorithms – Practice的笔记，是如何求解X的一系列算法正交匹配追赶（OMP）算法，LS_OMP算法，MP算法，weak_MP算法和阈值算法，对公式进行了推导。

A.正交匹配算法(OMP)

 对支持域中所有的j,计算出错误e(j)=min||ajzj-r||,找到一个最小的j0使得对于支持域内的任意j满足e(j0)<e(j)。然后把j0加入支持域中，计算支持域下的最优解(最小二乘法)，然后跟新残差，如果迭代次数达到一定值或者残差达到一定的值就停止。

B. MP匹配算法

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