tuxiangquzao

能实现数据的分类，权值的分布图形，但是权值及阙值的更改没有实现(Can achieve data classification, weight distribution of graphics, but the right values and the change did not achieve the Threshold)

matlab数据挖掘算法。实用cart决策树进行分类，可识别多类。decision tree algorithm, classification.(Matlab data mining algorithms. Practical cart decision tree classification, identification number category. Decision tree algorithm, the classification.)

用振幅为0.8的方波进行傅里叶分析，并求当K不同值时的合成信号。(By amplitude of 0.8 square wave to Fourier analysis, and pray for different value when K synthetic signal. )

提出了一种新的基于图像分块重构和线性判别分析相融合的方法，主要用于人脸识别。该方法通过计算两幅图像之间图 像块的重构均值误差，运用线性判别分析求出两幅图像降维后的欧式距离，融合重构误差和欧式距离计算这两幅图像之间的差别 程度。(A new block-based image reconstruction and the integration of linear discriminant analysis method is mainly used for face recognition. This method between the two images by calculating the reconstructed image block average error, calculated using the linear discriminant analysis after dimension reduction of two images Euclidean distance, the integration calculation of reconstruction error and the Euclidean distance difference between these two images level.)

说明：  AR模型预测，matlab环境下用AR谱估计算法实现AR模型谱估计(AR model prediction, matlab environment AR spectral estimation algorithm AR model spectrum estimation)

说明：  用ar方法估计功率谱，并估计信号频率和峰值(Ar method estimates the power spectrum, and estimate the signal frequency and peak)

bang zhu chu xue zhe dui jian dan de matlab cheng xu xue xi

CVPR2015级联CNN进行人脸检测的MATLAB实现代码，按照流程实现，效果绝佳(CVPR2015 cascade CNN for face detection MATLAB implementation code, according to the sequence, and excellent results)

为实现合成孔径雷达（SAR）图像分类算法的测试与评估，将VC/Matlab 混合编程技术应用到SAR 图像分类平台开发中，分析与 比较了4 种VC/Matlab 混合编程方法及各自优缺点，并着重研究了基于组件对象模型（COM）的VC/Matlab 混合编程方法。使用Matlab COM 编译器创建了SAR 图像分类算法组件，在VC 中调用其导出的接口函数。在此基础上，完成了SAR 图像分类平台的实例开发且 可脱离Matlab 环境运行。实验结果表明，该方法较好地发挥了VC 与Matlab 各自的优势，提高了SAR 图像分类平台开发的效率。(In order to test synthetic aperture radar （SAR） image classification algorithm，VC/Matlab mixed programming technology was used in SAR image classification platform development. Four VC/Matlab mixed programming methods were introduced and analyzed. Comparing with other three methods，the method based on component object model （COM） was studied particularly. SAR image classification algorithm component was created by Matlab COM complier，and its interface function could be invocated with VC. Using this method，a SAR image classification platform was realized. The platform could run without Matlab. The experimental result shows a good combination of VC and Matlab. So，developing efficiency could be enhanced a lot.)

felllow 学生 ，无线充电论文，挺好的 ，两篇SCI论文(Felllow student, wireless charging paper, very good, two SCI papers)