GSA

说明：  系统诊断，对系统诊断的编程，真的是对系统诊断的各种语言编程(System Diagnostics)

lbm palabos--格子波尔兹曼方法模拟开源软件，功能强大，也可在windows下用codeblocks 编译 在石油领域有重大应用(a open software of the lbm，and it is very useful in the field of petroleum)

本案例基于MATLAB的GUI工具进行设计仿真实验：通过对采集的车牌图像进行灰度变换、边缘检测、腐蚀及平滑等过程来进行车牌图像预处理，并由此得到一种基于车牌颜色纹理特征的车牌定位方法，实现车牌区域定位，最后实现车牌字符的分割与识别。(In this case based on MATLAB GUI design simulation tool: through the license plate image capture through gradation conversion, edge detection, corrosion and smoothing process for the license plate image preprocessing, and thereby obtain a color texture features based on license plate the method of license plate location, license plate positioning to achieve, and finally realize the segmentation and recognition of license plate characters.)

清华matlab图像处理大作业，其中人脸检测部分没有采用rgb而是采用hsv模型替代(Tsinghua matlab image processing large operation, which does not use face detection part rgb hsv model instead of using alternative)

关于采样数据得频谱分析MATLAB事例程序(Sampling data on a spectral analysis program MATLAB examples)

基于紧格式线性化方法与偏格式线性化方法，可将非线性系统线性化，后用PID控制，设计控制器(Based on tight format linearization method and partial format linearization method, nonlinear system can be linear, with PID control, to design the controller )

极限学习机（Extreme Learning Machine，ELM），该算法随机产生输入层与隐含层间的连接权值及隐含层神经元的阈值，且在训练过程中无需调整，只需要设置隐含层神经元的个数，便可以获得唯一的最优解。与传统的训练方法相比，该方法具有学习速度快、泛化性能好等优点(Extreme Learning Machine regression and classification, introduce a new algorithm for SLFN- Extreme Learning Machine (Extreme Learning Machine, ELM), the algorithm randomly generated input layer and hidden layer connection weights between the hidden layer and dollar threshold, and no adjustment in the training process, only need to set the number of hidden layer neurons, they can obtain a unique optimal solution.)

Impulse response of a continuous-time Gaussian filter

相机坐标变换标定矩阵的张正友算法，用于标定相机图像坐标与世界坐标的关系(Coordinate transformation matrix camera Zhengyou calibration algorithm used to calibrate the camera image coordinates and world coordinates relations)

本程序是用于在时域中分析处理轴承故障数据的，提取了各种时域的特征参数，包括均值，有效值，峭度，裕度指标，波形指标等等 适合初学者用于轴承的故障诊断中对参数的提取。（附上轴承故障数据3类共21组 正常、内圈、外圈）(This procedure is used in the time domain analysis of bearing fault data processing to extract the characteristics of various time domain parameters, including mean, RMS, kurtosis, margin indicators, wave indicators, and so suitable for beginners for bearings Fault diagnosis of parameter extraction.)