project

binary PSO islanding in distribution system

圆阵DOA估计，适合于初学圆阵的人，简单易用。(Circular array DOA estimation)

认知无线电中的频谱感知技术 包含单节点的检测和多点的写作检测(Spectrum-aware Detection of single-node Collaborative detection)

2013数学建模研究生B题建立多项式模型代码(2013 graduate of mathematical modeling to establish polynomial model code B title)

33节点配电网潮流计算，应用前退回带法，计算简单，收敛迅速(33 node distribution power flow calculation, before the return with the application method, the calculation is simple, rapid convergence)

一个身体部位比较模型的新方法网络（BAN）的，可以容纳多个环节和多个科目。所述的绝对测量允许跨频谱可能刻画的比较 从单参数为整个合奏，通过基于参数化到每个活动，每个学科和每个环节模型。使用错误，并明确之间权衡复杂性，在一个善良的适应措施相结合，显示有重要的影响时，适用于一系列典型的禁止通道数据。它是有不同的 在模式的选择的影响，以及它相关的复杂性，混合活动的“日常”的数据，设置活动相比，动态数据（例如步行）。平均路径损耗的不足，甚至位数的路径损失的措施，作为唯一的表征还强调“禁止通道。 (A new approach to compare models for body area networks (BAN) that accommodates multiple links and multiple subjects is presented. The absolute measure described allows comparison across a spectrum of possible characterizations ranging from single-parameter for an entire ensemble, through to per-activity, per-subject and per-link based parameterized models. The use of an explicit trade-off between error and complexity, combined in a goodness-of-fit measure, is shown to have important consequences when applied to a range of typical BAN channel data. It is shown that there are different implications in choice of model, and it’s associated complexity, for mixed-activity “everyday” data, when compared with set-activity dynamic data (e.g. walking). The deficiency of mean path loss, or even median path loss measures, as a sole characterization of the BAN channel is also highlighted.)

风机建模。在matlab的simulink环境下，对永磁同步风机进行了建模。(Fans modeling. In the simulink matlab environment, the permanent magnet synchronous wind turbine is modeled.)

用经典龙格-库塔法和变步长的龙格-库塔法求解微分方程(Classical Runge- Kutta method and the variable step Runge- Kutta method for solving differential equations)

用 MATLAB 编写的 免疫算法源程序 比较实用。希望对大家有所帮助。算法很好。(using MATLAB immune algorithm source more practical. We want to help. Algorithm good.)

The Driven Cavity Problem by the MAC Method