Breastcancer

This is PCA source. please contact me if you have some question.

基于MATLAB神经网络，利用165期双色球数据建立预测模型网络(Based on MATLAB neural network using 165 color ball prediction model data network)

基于局域均值的盲源分离技术在故障诊断中的应用文章，希望对大家有用！(Based on Local Mean Blind Source Separation Techniques in Fault Diagnosis article, I hope useful for everyone!)

Gabor小波变换与PCA的人脸识别代码，可实现对二维数据的聚类，IMC-PID是利用内模控制原理来对PID参数进行计算。( Gabor wavelet transform and PCA face recognition code, Can realize the two-dimensional data clustering, The IMC- PID is using the internal model control principle for PID parameters is calculated.)

Myplotyy情节不同的数据集具有共同的X轴使用一个数字，但个别的Y轴。 每一个曲线（Y轴）的属性可单独调整，为线性或对数尺度，正常或反向规模，置信区间等，颜色，曲线标签，... 见截图和运行示例“myplotyy_example.m”在zip文件中。 (Myplotyy plots different data sets with a common x-axis but using individual y-axes in one figure. The properties of every curve (y-axis) can be individually adjusted, such as linear or logarithmic scale, normal or reverse scale, confidence intervals, colors, curve labeling, ... See screenshot and run the example "myplotyy_example.m" included in the zip-file. )

matlab产生高斯脉冲matlab产生高斯脉冲(matlab matlab generated Gaussian pulse generated Gaussian pulse)

粗糙集理论的属性约简方法及应用研究，很有用的哈！！！！(Rough set attribute reduction method and application, very useful, ha! ! ! !)

说明：  基于DCT的水印图像matlab代码，主要是水印嵌入和水印提取两大主要部分(DCT-based image watermarking matlab code, mainly watermark embedding and watermark extraction are two main parts)

This is a useful book for beginners in MATLAB

谱聚类算法建立在谱图理论基础上，与传统的聚类算法相比，它具有能在任意形状的样本空间上聚类且收敛于全局最优解的优点。 该算法首先根据给定的样本数据集定义一个描述成对数据点相似度的亲合矩阵,并且计算矩阵的特征值和特征向量 ， 然后选择合适 的特征向量聚类不同的数据点。谱聚类算法最初用于计算机视觉 、VLS I 设计等领域， 最近才开始用于机器学习中，并迅速成为国际上机器学习领域的研究热点。(Spectral clustering algorithm based on the reproduction diagram theory, compared with the traditional clustering algorithm, it can have on the arbitrary shape of sample space clustering, and the advantage of converge to global optimal solution.The algorithm firstly according to the given sample data set defines a description of the data points of similarity in pairs of affinity matrix, and computing the matrix eigenvalue and characteristic vector, and then choose the appropriate feature vector clustering of different data points.Spectral clustering algorithm was originally used in computer vision, VLS in areas such as design, I recently started used in machine learning, and quickly became a hot issue in the field of international machine learning research.)