一种很重要的非监督降维方法，是流形学习算法Laplacian Eigenmap 的线性化方法，在人脸识别中效果非常好。,A very important method of unsupervised dimensionality reduction, manifold learning algorithm is Laplacian Eigenmap linearization method is very effective in face recognition.

介绍基于神经网络的反馈线性化控制过程。反馈线性就是利用反馈的控制手段来消除系统中的非线性，以使的其闭环系统的动力学方程是线性的。-Introduced based on neural network feedback linearization control process. Feedback linearization is to use feedback control to eliminate the non-linear system, so that its closed-loop

流形学习算法lle的线性化方法，是一种非监督的降维方法，比lle的优势在于可以将新的样本点映射到低维空间。-Lle manifold learning algorithm of the linearization method, is a non-supervised dimensionality reduction method has the advantage of being more than lle can sample the new point is mapped to the

神经网络控制工具箱,包括最优控制,反馈线性化控制,预测控制-Neural network control toolbox, including optimal control, feedback linearization control, predictive control