DEMOBOT

falsa posicion by davo

扩展卡尔曼滤波，一种非线性滤波，可用于目标跟踪，初学者适用(Extended Kalman filter, a nonlinear filtering, can be used for target tracking, suitable for beginners)

含风电场的电力系统潮流计算吴义纯caj IEEE14节点数据的说明(With the wind farm power flow calculation WU Yi pure. Caj)

Cyclostationary feature analysis

singer模型，很好的目标跟踪代码，经测试好用(singer model, good target tracking code has been tested and easy to use)

说明：  清华大学电子系谷源涛老师MATLAB课件及演示程序，简明扼要。(Department of Electronics, Tsinghua University, Tao Gu source courseware and teacher MATLAB demonstration program, clear and concise.)

雨流计数和疲劳寿命估算,用于统计自己获取的信号，得到载荷谱，进行疲劳计算(Rain flow count and fatigue life estimate, used to calculate the signal obtained by their own, get the load spectrum, fatigue calculation)

说明：  摘要地层控制分析与设计问题 无人机（UAV）群系统实现时间。 研究了不同的地层。达到预定时间- 无人机的编队、编队协议各不相同。 首先是群系统，无人机的速度可能不同 当到达编队时。然后，基于共识的方法 用于处理时变信息的形成控制 无人机群系统的问题。必要和充分 无人机群系统实现时变的条件 提出了构造方案。(Abstract-formation control analysis and design problems for unmanned aerial vehicle (UAV) swarm systems to achieve time. varying formations are investigated. To achieve predefined time- varying formations, formation protocols are presented for UAV swarm systems first, where the velocities of UAVS can be different when achieving formations. Then, consensus-based approaches are applied to deal with the time-varyin formation control problems for UAV swarm systems. Necessary and sufficient conditions for UAV swarm systems to achieve time-varying formations are proposed.)

说明：  公共交通最佳路径算法在分析城市道路网络最短路径算法 SP算法 和公交网络的特点的基础上,提出公共交通系 ( ) ( ) 统最佳路径算法.首先引入直达矩阵 T矩阵 和最小换乘矩阵 Q 矩阵 ,讨论公交网络节点间换乘 问题,得出最少换乘算法.利用 Q 矩阵确定节点间最少换乘次数,评价公交网络方便可达性.其次 ( ) 结合最少换乘算法,对最短路径算法 Dijkstra 算法 进行改进.在标号过程中,利用 Q 矩阵对待检验 T标号点进行筛选,减少 T 标号计算量,得到一条综合考虑路径长度和换乘的最佳路径.最后用一 个简单的算例进行验算,说明该算法适用于一般公交网络,特别是换乘代价较高的公交网络.(Public transport system the best path algorithm )

％this program is written by 刘学智. Finished time is 05.1.23 16:03 ％utilizing it solving TSP problem by simulating stealing algorithm ( This program is written by Liu Xuezhi. Finished time is 05.1.23 16:03 utilizing it solving TSP problem by simulating stealing algorithm)