An intelligent optimization algorithm for service providers

说明：  mdsb matlab

说明：  遗传算法解非线性方程组，搞了好久了，希望能帮到大家(Genetic algorithm for solving nonlinear equations, out for a long time, and hope can help you)

td-scdma中用QPSK调制后的解调(QPSK demudulation)

Model of electric drive with DC machine controlled in closed loop

计算层合板刚度，和最先一层失效载荷！程序具有通用性，能够对任意工程弹性常数和几何尺寸的层合板进行刚度和强度分析！非常适合最为哈尔滨工业大学复合材料与工程专业的复合材料力学上机大作业(Laminate stiffness calculation, and the first layer of failure load! Program is versatile, capable of any engineering elastic constants and geometry of laminates for stiffness and strength analysis! Very suitable for most Harbin Institute of Technology composite materials and engineering mechanics of composite materials on the plane big job)

说明：  在这个知识库中，图形信号处理的一些有趣的特性被表示出来。演示通过经典信号处理和图形信号处理对一维和二维欧几里得域信号应用低通滤波器，比较两种方法的结果。在此基础上，验证了图形信号处理的工作机制。此外，还描述了在非欧几里得域上滤波信号的示例。(In this repository, Some fascinating features of Graph Signal Processing were represented. Demos incudes applying a low-pass filter on both 1D and 2D euclidian domain signal by classical signal processing and also Graph signal processing to compare both results are the same. Within that way, we will validate the working mechanism of Graph Signal Processing. In addition to this, an example of filtering a signal on the non-euclidian domain was also represented.)

样本熵MATLAB程序，希望可以共享。 此程序可以计算脑电信号EEG的样本熵的值，可以作为脑电信号分析之用。(samples entropy MATLAB procedures in the hope that can be shared. This procedure can be calculated EEG EEG samples entropy value, as EEG analysis.)

针对PID控制模型，使用模糊控制方法对PID的参数自适应优化，属于基于模糊自适应PID控制算法程序(For the control of the PID model, using the parameter optimization of adaptive fuzzy control method for PID, which belongs to the fuzzy adaptive PID control algorithm program based on)

对地震数据进行逆F-K变换，得到的结果变回到时间域(The inverse F-K transform of seismic data is returned to the time domain.)

转：https://blog.csdn.net/jinshengtao/article/details/26278725 混合高斯背景建模是基于像素样本统计信息的背景表示方法，利用像素在较长时间内大量样本值的概率密度等统计信息(如模式数量、每个模式的均值和标准差)表示背景，然后使用统计差分(如3σ原则)进行目标像素判断，可以对复杂动态背景进行建模，计算量较大。 在混合高斯背景模型中，认为像素之间的颜色信息互不相关，对各像素点的处理都是相互独立的。对于视频图像中的每一个像素点，其值在序列图像中的变化可看作是不断产生像素值的随机过程，即用高斯分布来描述每个像素点的颜色呈现规律单模态(单峰)，多模态(多峰)(Gaussian mixture background modeling is a background representation method based on the statistical information of pixel samples. Statistical information such as the number of patterns, the mean and standard deviation of each pattern are used to represent the background. Statistical difference (such as 3_principle) is used to judge the target pixel. Complex dynamic background modeling has a large amount of computation. In the Gaussian mixture background model, it is considered that the color information between pixels is uncorrelated and the processing of each pixel is independent of each other. For each pixel in a video image, the change of its value in a sequential image can be seen as a random process that produces pixel values continuously, i.e. Gaussian distribution is used to describe the regularity of color rendering of each pixel in single mode (single peak) and multi-mode (multi-peak).)