real_time_model

power system tools for study of power systems load flow and stability small signal

C. Torrence博士在分析厄尔尼诺现象时的示例程序，包含小波的重构部分，非常经典，该文被引用超过2400次(C. Torrence Dr El Nino phenomenon in the analysis of the sample program, including reconstruction of part of the wavelet, very classic, the paper cited more than 2400 times)

说明：  三项交流同步电机的仿真 已经调试过了 可以使用(3 AC synchronous motor simulation has been debugging can use)

使用Matlab对一集体函数进行fft计算，并绘制复制图像，并减小栅格效应(Using Matlab fft function on a collective basis, and draw copy the image and reduce the effect of the grid)

仿真不同占空比，等概、非等概双极性矩形随机信号的归一化功率谱密度，分析不同信号所包含的频谱分量，有无直流分量和定时分量信息 (Simulation different duty cycles, etc. There is, and so there was a non-random signal bipolar rectangular normalized power spectral density analysis of the spectral components of different signal contained, with or without DC component and timing component information)

说明：  这是一个基于MATLAB的三相SPWM逆变电路(This is a MATLAB-based three-phase SPWM inverter circuit)

展示了线性、DFE、MLSE均衡器的信噪比性能，并通过蒙特卡罗模拟信道估计结果确定。(This demo shows the BER performance of linear, decision feedback (DFE), and maximum likelihood sequence estimation (MLSE) equalizers when operating in a static channel with a deep null. The MLSE equalizer is invoked first with perfect channel knowledge, then with an imperfect, although straightforward, channel estimation algorithm. The BER results are determined through Monte Carlo simulation. The demo shows how to use these equalizers seamlessly across multiple blocks of data, where equalizer state must be maintained between data blocks. )

基于matlab的fcm（模糊C）图像分割代码，适于matlab和图像分割入门学习(failed to translate)

完整的循环谱计算代码，可以直接运用，稍加改动就可以变成其他的循环谱形式，欢迎下载。(Complete cycle spectrum calculation code can be directly applied, a little change can become another form of cyclic spectrum, welcome to download.)

遗传算法是模拟达尔文的遗传选择和自然淘汰的生物进化过程的计算模型。它的思想源于生物遗传学和适者生存的自然规律，是具有“生存＋检测”的迭代过程的搜索算法。遗传算法以一种群体中的所有个体为对象，并利用随机化技术指导对一个被编码的参数空间进行高效搜索。(Genetic algorithm is simulated Darwinian natural selection of genetic selection and evolution process model. It' s thought from biological genetics and survival of the fittest laws of nature, is a " survival+ detection" iterative process of search algorithm. Genetic algorithms in a group all the individuals targeted, and technical guidance on the use of a randomized coded efficiently search parameter space.)