Hallen3

独立成分分析算法，定点独立成分分析。可以用于图像特征提取(fastica algorithm)

Iterative closest poin in MATLAB

Principal component analysis (PCA) is a popular tool for linear dimensionality reduction and feature extraction. Kernel PCA is the nonlinear form of PCA, which is promising in exposing the more complicated correlation between original high-dimensional features. In this paper, we first talk about the basic ideas of PCA and kernel PCA, and then focus on the reconstruction of pre-images for kernel PCA. We also give an introduction on how PCA is used in active shape models (ASMs), and discuss how kernel PCA can be applied to improve traditional ASMs. Then we show some experiment results to compare the performance of kernel PCA and traditional PCA for pattern classification. We also implement the kernel PCA-based ASMs, and use it to construct human face models.

认知无线电主用户信号为BPSK信号在不同信噪比下的检测概率和虚警概率(Cognitive radio primary user signal is BPSK signals in different SNR detection probability and false alarm probability)

用matlab做三角单元的有限元分析，很有用，代替手算，十分方便快捷。(Finite element analysis of triangular element with MATLAB )

直方图均衡化，数字图像处理，简单matlab函数(Histogram equalization, digital image processing, a simple matlab function)

说明：  灰度共生矩阵和灰度梯度共生矩阵提取纹理特征，用matlab实现的(Graylevel co-occurrence matrix and grayscale gradient co-occurrence matrix extraction means)

时频分析方法中的伪——威格尔分布，可用于信号处理。(Time frequency analysis of v-Weigel distribution method, which can be used for signal processing.)

说明：  数学建模中的图论知识来研究最短路径的问题，利用Dijkstra算法matlab实现(Graph theory knowledge in mathematical modeling is used to study the shortest path problem, which is realized by using Dijkstra algorithm matlab.)

some thing more for MIMO