VAHAB

在OFDM仿真模型的基础上用MATLAB语言编写出OFDM发送、信道及接收整个系统,在系统仿真正确的前提下,对循环前缀、信道估计等性能改善方法进行进一步仿真验证,得到了预期的理想结果 (In OFDM simulation model based on the use of MATLAB language to send the OFDM, channel and receive the entire system, in the system under the premise of the correct simulation of the cyclic prefix, channel estimation methods for further performance improvement simulation, have been expected results)

高斯白噪声产生程序文件，直接可用有注释 对于初学者有帮助(Gaussian white noise generated files, can be annotated directly helpful for beginners)

说明：  本算法为用遗传算法改进粒子群GA-PSO算法，附带含有程序使用说明。(This algorithm uses genetic algorithm to improve particle swarm optimization GA-PSO algorithm, with instructions for the use of the program.)

Quarteroni的计算数学，包含内容非常广泛，除了经典的数值分析内容，还有不少偏微分及网格划分。(Contains the content is very extensive, in addition to the content of classical numerical analysis, there are a lot of partial differential and mesh.)

这个是matlab下时频分布处理的全部代码。(under Matlab is the time-frequency distribution of all the code.)

异步电动机矢量控制模型，simulink仿真模型，matlab虚拟实现(Vector control induction motor model, simulink simulation model, matlab Virtual Reality)

輸入點位於WGS84之大地經、緯度，可於命令窗顯示此點之卯酉圈曲率半徑N、子午圈曲率半徑M及平均曲率半徑R及此點之空間直角坐標X、Y及Z。(Input point is located in the WGS84 geodetic latitude and longitude can be displayed in the command window of the prime vertical radius of curvature point N, M meridian radius of curvature and the average radius of curvature R and the point of the space rectangular coordinates X, Y and Z.)

this is about inverter control and it is developed in matlab/simulink envirnovement

基于matlab GUI界面设计,LYYWKyo参数数学方法是部分子空间法，采用了小波去噪的思想，BP神经网络用于函数拟合与模式识别，PnTuuBt条件包含特征值与特征向量的提取、训练样本以及最后的识别，包括主成分分析、因子分析、贝叶斯分析。( Based on matlab GUI interface design, LYYWKyo parameter Mathematics is part of the subspace, Using wavelet denoising thought, BP neural network function fitting and pattern recognition, PnTuuBt condition Contains the eigenvalue and eigenvector extraction, the training sample, and the final recognition, Including principal component analysis, factor analysis, Bayesian analysis.)

The model used for creating the reference voltage is shown in Fig. 4. First, photovoltaic output current (Ipv) and output voltage (Vpv) are passed through a first order low pass filter with a magnitude of G = 1 and a time constant of T = 0.01 seconds in order to filter out the high frequency components or harmonics from these signals as shown in Fig. 5 and Fig. 6. The filtered current and voltage signals (Ipv_F and Vpv_F) are then fed into the MPPT control block that uses the Incremental Conductance Tracking Algorithm. An algorithm that is based on the fact the slope of the PV array power curve shown in Fig. 7 is zero at the Maximum Power Point (MPP), positive on the left of the MPP, and negative on the right. The MPP can thus be tracked by comparing the instantaneous conductance (I/V) to the incremental conductance (∆ I/∆ V) [11] as in (1):