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基于边界元与有限元耦合的地震动模拟程序。能简单有效的解决地震作用下地表位移反应问题(Based on boundary element and finite element coupled to ground motion simulation program. Can be simple and effective solution surface displacement response under earthquake problem)

整数规划的matlab代码，常用的优化工具！(Integer programming matlab code, commonly used optimization tools!)

小波消噪及其在往复泵振动监测信号处理中的应用(The wavelet denoising its reciprocating pump vibration monitoring signal processing)

a simple eigenface program under matlab Imagetest is the picture of the guy you want to find among the 20 guys

说明：  MeanShift算法在运动人体跟踪MATLAB代码(MeanShift algorithm in MATLAB code tracking of moving body)

creat text file in matlab for example you can export your result in txt format

针对mean shift 跟踪方法中存在的光照变化不稳定问题， 提出了基于梯度特征与彩色 特征相融合的mean shift 跟踪方法。首先分别提取目标的梯度特征和彩色特征，利用多尺度的相似度 计算方法进行特征的匹配，然后通过最大化相似度对目标进行跟踪。通过物体和人体等运动目标的跟 踪，验证了改进的跟踪算法在光照变化情况下的鲁棒性优于原有的算法，显著降低了跟踪位置误差。(The instability of the light changes in the mean shift tracking method, the mean shift tracking method based on gradient features and color characteristics of fusion. First extract gradient features and color features of the target, the similarity calculation method using multi-scale feature matching, and then maximize the similarity of the target track. Through the tracking of objects and people moving target, verify the robustness of the improved tracking algorithm in the case of illumination changes is better than the original algorithm significantly reduces the tracking position error.)

Modal Analysis for hydropower generation

对网络划分社区,并找出最大的社区,很有用的程序(Find the largest giant component)

支持向量机是用于分类与回归的技术。由于其自身的诸多缺点，如无法获得概率输出，需要估计一个误 差参数C，以及必须使用Mercer 核函数等。相关向量机算法，克服了SVM 上述缺点，RVM 能获得与SVM 相比拟的推 广性能，并且更为稀疏。在此基础上，文中介绍了一种RVM 回归用于分类的新分类方法，用RVRC 来表示。并通过 实验证明了它的可行性。(Support vector machines for classification and regression techniques. Due to its many shortcomings, such as the probability that the output can not be obtained, need to estimate an error parameter C, and the need to use Mercer kernel function and so on. Relevance vector machine algorithm to overcome these shortcomings of SVM, RVM and SVM can be obtained comparable to promote performance and more sparse. On this basis, the paper introduces a RVM regression was used to classify new classification method, RVRC to represent. And through experiments proved its feasibility.)