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Laplacian Eigenmaps [10] uses spectral techniques to perform dimensionality reduction. This technique relies on the basic assumption that the data lies in a low dimensional manifold in a high dimensional space.[11] This algorithm cannot embed out of sample points, but techniques based on Reproducing kernel Hilbert space regularization exist for adding this capability.[12] Such techniques can be applied to other nonlinear dimensionality reduction algorithms as well.

用matlab实现三类三维的特征选择，效果特别好(feature selection code of matlab)

说明：  鲸鱼算法优化支持向量机，可用于类预测，测试可用(Whale optimization algorithm optimization support vector machine)

本程序描述了无导师学习的神经网络用于一般的分类问题(This procedure describe no mentor learning neural network used for general classification problem)

Uniform subset selection with Kennard and Stone algorithm in Matlab

matlab实现黄金分割法求非线性函数的极值问题，含实例(MATLAB Golden Section min)

时域自适应滤波中基于后验概率的格型RLS算法(奀郖赻巠crown thinning recommended price笢Guang Ya Carex quilt is made up of trace倰cavity RLS呾Yang)

说明：  声音信号 显示 时域 频域 对声音的预处理观察

说明：  用matlab实现的图像配准的小程序，一个缩放图像，一个配准(Using matlab to achieve a small image registration procedure)

一篇文献，模糊控制及其matlab应用，文章很好，值得一读(One paper, fuzzy control and its application matlab)