huamoMATLAB

代码实现对图形的锐化处理，具有图形界面按键选择Roberts交叉算子、Sobel算子、Laplace边缘增强算子对图像进行锐化处理。(failed to translate)

利用matlab计算copula函数的代码及程序，希望可以给大家带来帮助(Copula function calculated using matlab code and procedure, hoping to give us help)

基于分水岭算法源程序含文章，可有效分割处图像(Based watershed algorithm source code containing the article, which can effectively split at the image)

Gaussian pyramidal model using Matlab

维纳滤波复原,规则化滤波复原程序,Lucy-Richardson复原程序举例,盲去卷积复原,逆滤波复原算法(Wiener filter restoration, rules-based filtering for restoration procedures, Lucy-Richardson restoration program for example, blind deconvolution restoration, inverse filtering restoration algorithm)

FEC decoding algorithm for Reed Solomon

INS/DVL 组合导航 已收敛 有贯导就、四元素解算 航姿校正(INS/DVL integrated navigation convergence has consistently guide on the four-element solver AHRS correction)

第12章 解线性方程组的迭代法.zip。是从书中光盘里直接拷贝的代码，放在这里，与大家共享，共同交流，希望对大家有帮助。(Chapter 12 solution of linear equations of the iterative method)

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.

计算常用指标Gmean,F-score,sensitivity,specificity,precision,roc和auc曲线，输入test_label,predict_label两个列向量，即可获得以上指标(calculate some indexes)