tdm_figure

4DPSK, 8DPSK在高斯信道下性能仿真. 解调方式不仅包括包括相干解调,还有个人编写的非相干解调,对于急需非相干解调的很有帮助(4DPSK, 8DPSK in Gaussian channel performance simulation. Demodulation not only include coherent demodulation, there are individuals prepared by non-coherent demodulation, the urgent need for non-coherent demodulation of the useful)

说明：  首先从微电源、储能元件、负荷各方面对微网建模展开研究,并在对现有的电力系统随机潮流算法进行全面对比分析的基础上,重点研究了基于半不变量及Gram-Charlier级数的随机潮流算法,将其应用于微网的随机潮流计算分析中。(Firstly, micro-grid modeling is studied from the aspects of micro-power supply, energy storage components and load. On the basis of comprehensive comparative analysis of existing power system stochastic power flow algorithms, the stochastic power flow algorithm based on semi-invariant and Gram-Charlier series is studied, and applied to the stochastic power flow calculation and analysis of micro-grid.)

用MATLAB编写的利用有限差分时域法仿真电磁带隙天线的代码，非常有用(EBG Antenna analysis based on FDTD using matlab)

说明：  BP神经网络用与实现不同故障的分类，对复杂信号模式识别是一种很有效的方法。(BP neural network with the classification of different faults and implementation of complex signal pattern recognition is a very effective method.)

说明：  可以使用SVM、LSSVM算法对样本集进行模式识别和去噪等操作(SVM and LSSVM algorithms can be used for pattern recognition and denoising)

数值分析，上机题目，求解方程组十分方便 数值分析，高斯公式， 求解方程组十分方便(Numerical analysis, the machine topic is very convenient for solving equations numerical analysis, Gaussian formula is very convenient for solving equations)

可以实现粗糙集的整个算法，从上下近似、属性约简、属性重要度到决策规则的输出和规则的确定性因子，全部实现。内附测试数据，有详细的注解，可以实现与数据库的直接连接。(Rough set can be achieved throughout the algorithm, from top to bottom approximation, attribute reduction, attribute importance to the uncertainty factor output of decision rules and regulations, all to achieve. Enclosing the test data, detailed notes, can be achieved with a direct connection to the database.)

说明：  l雷诺方程离散求解的基本思路以及程序编写思路(The finite difference method of Reynolds equation and the realization of related programs)

基于二乘法的参数辨识，通过输入输出数据，求得所需辨识的系统参数(Squares-based parameter identification, input and output data, to obtain the required identification system parameters)

这是基于压缩感知的MP算法，经本人验证仿真，没得问题(This is based on the the compressed sensing MP algorithm, after I verify the simulation, did not have the problem)