三相异步电机经典的参数辨识MATLAB仿真模型

用matlab软件编写的可以模拟森林发生火灾时，树木的燃烧情况(It can be used to simulate forest fires)

说明：  赛码网计算机专业毕业生的求职资料，上传的资料主要是华为篇。希望可以对各位求职者有所帮助。(The information uploaded by the computer graduates of Cyber Network is mainly Huawei Chapter. I hope it can be helpful to all job seekers.)

协同区间偏最小二乘 siPLS算法是 N rgaard等对其提出 的 iPLS方法的改进, 其基本算法步骤如下:(1)对原始谱图进行 预处理;(2)在全谱范围内建立全局偏最小二乘模型, 即上节的 模型;(3)在整个光谱区间采用 iPLS建立多个等窗口宽度的子 区间, 假设为 n个;(4)在每个子区间上建立偏最小二乘法模型, 即可得到 n个局部模型;(5)以交叉验证时的均方根误差 RMSE 值为各模型的精度衡量标准, 比较全光谱模型和各局部模型的 精度;(6)组合精度最高的局部子区间为新的回归区间;再在新 的回归区间建立 siPLS模型(Cooperative interval partial least squares (siPLS) algorithm is proposed by N rgaard et al. The improvements of the iPLS method are as follows: (1) the original spectrogram is performed. Preprocessing; (2) establishing a global partial least squares model in the full spectrum, that is, the upper part of the model. Model; (3) use iPLS to establish multiple equal window widths in the whole spectral interval. The interval is assumed to be n; (4) a partial least squares model is established on each sub interval. N local models can be obtained; (5) the root mean square error of cross validation is RMSE The values are the accuracy criteria of each model, and the comparison between the full spectral model and the local models is made. (6) the local interval with the highest combined precision is a new regression interval; and then new. The establishment of siPLS model in the regression interval)

大家好 这个代码是为了运行一个雷达的程序 很好用的 希望大家喜欢(hello we hope everyone likes it)

一款局域网工具，能进行点对点传送文件，还可以通信-A local area network tools, can be point-to-point transmission of documents, but also communication

dreamweaver插件3-Dreamweaver plug-3

说明：  复选框和单选按钮的插件。它使用纯CSS编写，没有任何(Plug-ins for check boxes and radio buttons. It is written in pure CSS, without any.)

单目标的ego全局优化优化算法啊啊啊啊啊(Ego global optimization algorithm with single objective)

SVC code with PSO and GA comparision

基于压缩感知的图像处理，应用了OMP cosamp romp SAMP 几种压缩感知算法并对其进行了对比分析(Based on compressed sensing image processing, we applied OMP CoSaMP romp SAMP several compressed sensing algorithms and compared them.)