ELM代码

一个计算用的matlab小程序，希望大家喜欢，谢谢(A calculation of the matlab small program I hope you like it, thank you)

fastica算法实现忙元分析的算法，matlab编程

比较全面的介绍matlab处理图像图形的命令，以及相关的说明和实例(More comprehensive introduction matlab image processing graphics commands, and related instructions and examples...)

Side impact accidents against a tree or pole remainthe most dangerous accident scenarios in rally cars. Statistical data shows that 52 of the fatalities between 2004 and 2009 concern crashes against a rigid pole by the track sides, whilst among those more than 60 were side impacts. Despite the present scientific efforts, rallying cars side impacts are still among the least understood primarily due to limited space between the occupant and door sill, evolving safety regulations and vehicle dynamics.

matlab_入門程式範例台灣大學張智星教授撰寫(matlab entry program examples)

emd算法 主要用来提取信号的本征模态，将信号的原始信号从混合噪声中提取出来(emd algorithm Mainly used to extract the signal intrinsic mode, the original signal from the mixed noise extraction)

激光雷达点云滤波的topscan算法实现，并能计算精度，绘制出地面点效果图。(Topscan LIDAR point cloud filtering algorithm implementations, and can calculate the precision ground points plotted renderings.)

MATLAB环境中的KSVD字典学习，可以用于信号特征的分析，学习。(The KSVD dictionary MATLAB environment study, can be used for the analysis of characteristics of signal.)

Signal subspace identification is a crucial first step in many hyperspectral processing algorithms such as target detection, change detection, classification, and unmixing. The identification of this subspace enables a correct dimensionality reduction, yielding gains in algorithm performance and complexity and in data storage. This paper introduces a new minimum mean square error-based approach to infer the signal subspace in hyperspectral imagery. The method, which is termed hyperspectral signal identification by minimum error, is eigen decomposition based, unsupervised, and fully automatic (i.e., it does not depend on any tuning parameters). It first estimates the signal and noise correlation matrices and then selects the subset of eigenvalues that best represents the signal subspace in the least squared error sense. State-of-the-art performance of the proposed method is illustrated by using simulated and real hyperspectral images.

well-designed user work with in MATLAB, suitable for beginners