gmm

active shape model的matlab代码实现，用于图像处理，模式识别等方面(active shape model of matlab code for image processing, pattern recognition, etc.)

恒润科技，matlab手册，里面有matlab相关模块的介绍，可以说面面俱到，很详细。(Hengrun technology, matlab manuals, which have matlab introduce relevant modules can be said to be comprehensive, very detailed.)

自然激励下建筑结构的模态参数识别，首先通过自然激励技术（next）得到结构的自由响应，然后由自回归滑动平均（arma）方法识别模态参数。(natural incentive structures under the modal parameter identification, First through natural incentive Technology (next) to be free to respond to the structure, then autoregressive moving average (arma) identified modal parameters.)

matlab环境下的复杂网络小世界模型，M文件，可画图(small world in Matlab)

非线性函数拟合——利用遗传算法来优化BP神经网络，利用神经网络开发包实现图形化的神经网络模拟，使得神经网络原理更直观，可用于教学，也可用于实际神经网络训练，内附详细帮助文件。(Non-linear function fitting- using genetic algorithms to optimize the BP neural network, neural network development package to implement graphical neural network simulation, neural network theory makes more intuitive, can be used for teaching, but also can be used for the actual neural network training, in with detailed help files.)

说明：  涵盖机械设计课程设计的几乎所有内容，如执行机构（连杆、滑块等）、传动机构（带、链、齿轮、蜗杆、轴、轴承等）的设计与校核。(Covers almost everything in mechanical design course design, such as the design and verification of actuators (links, sliders, etc.) and transmission mechanisms (belts, chains, gears, worms, shafts, bearings, etc.).)

说明：  该程序可以求得任意两个长度相同的离散信号的互相关系数以及自相关系数，并绘制其图像(The program can get the cross-correlation coefficient of any two discrete signals with the same length, and draw the image of the cross-correlation coefficient)

c++priemer第三版，中文完美翻译，超好，希望对大家有用(c++ priemer third edition, Chinese perfect translation, super good, I hope useful for everyone)

Robust Non-negative Dictionary Learning for Visual Tracking The provided codes could be either embedded into the benchmark framework of paper Online Object Tracking: A Benchmark (CVPR2013) (You can find details here: http://visual-tracking.net/) or run on individual sequence. To run the benchmark, just put the entire folder into the /trackers folder in the benchmark code base, and modify the configTrackers.m in util folder. DLT gets an AUC of 0.436, which ranks 5th among 26 in the benchmark by 19/03/2014. We don t tune parameters for single sequence in this case, all the parameters are stored in trackparam_DLT.m. To run on individual video, you need to modify the dataPath and title in run_individual.m. If you run MATLAB version after 2012, and have a CUDA compatible GPU installed, you may enjoy the fast computation speed by GPU, just set useGPU to true in trackparam_DLT.m and run_individual.m!

network security algorithm ceasar cipher codes, simple implementation