matlab-learning

用于降低方向图旁瓣电平的基于遗传算法的唯相加权(Based on Genetic Algorithms phase-only weighting pattern used to reduce the side lobe level)

多重分形谱算法，多重分形MATLAB代码，多重分形谱代码(Multifractal spectrum algorithm)

上面都是最新的LDPC编码技术，希望对大家都有用哈，我觉得十分的有用(The above are the latest LDPC coding techniques, I hope everyone Ha, I think is very useful)

ROBOTICS IEEE PAPERS

随机信号功率谱估计，在频域对信号进行分析，用Matlab编程(Random signal power spectrum estimation using Matlab programming)

优秀论文及配套源码。电压暂降是动态电能质量问题中最受关注的热点之一。大量新型电力电子设备的广泛使用对电网电能质量的要求越来越高，而且电压暂降在电网中又具有一定的传播性。因此，无论从电网还是用户都迫切需要对电压暂降进行研究和治理。对电压暂降的检测是解决电压暂降的前提条件，故本论文主要对电压暂降的检测方法进行研究。 本文分析了国内外短时电能质量扰动检测的研究现状，并着重讨论了短路故障、感应电动机启动和变压器激磁三种电压暂降扰动情况下电压暂降的特性；在此基础上选择了基于S变换的短时电能质量扰动检测方法，从S变换的结果S模矩阵及S复矩阵中提取出所需数据并以此来对各种扰动情况下的电压暂降的幅值、相位跳变、持续时间和谐波含量进行分析。仿真结果表明，该方法很好地实现了对电压暂降各特征量的检测。 (The voltage sag is one of most hot topics in dynamic electric energy problems. Masses of new power and electron facilities have been put into use widely, requiring a high quality of electric network and power, chiefly the voltage sag. Moreover, the voltage sag can spread in the electric network. So people have every reason to research and control the voltage sag. However, before developing the voltage sag, people have to detect it. On account of the above, this essay will chiefly focus on the detect methods of the voltage sags. In this paper, the status of the short duration power quality disturbance based on the different method are researched firstly, and emphasizes the characteristic of the voltage sag under the situation of the three kinds of voltage sag disturbances like the short circuit fault, induction motor start-up and transformer excitation. On the basis of the above, the short duration power quality disturbance detection method based on S transform is chosen. The complex m)

lmmse file lest mean square algoritham materal

灰色预测，用于短期预测，所需数据少，实用，简单(Grey Forecasting)

BOOST CONVERTER USING ARDUINO

说明：  遗传算法的理论与讲解，还有部分代码设计与实现 相关遗传算法的改进也有详细的介绍(Theory and explain the genetic algorithm, part of the genetic code design and implementation of related algorithm is also introduced in detail)