Signal_Detection_and_Estimation

A matlab source code to simulate the Go Back N protocol.

dtcwt and bicubic based image resolution enhancement

遗传算法的JAVA实现 做了一个简单函数优化示例~~~~~~体现了面向对象思想(JAVA realization of genetic algorithm to do a simple example of function optimization ~~~~~~ reflects the object-oriented thinking)

本程序实现了哈夫曼编码，可以应用在图像处理中压缩图像，属于无损压缩！(huffman)

fuzzy system control,unstable system

信号盲源分离，非负矩阵分解，解决初值问题(Signal blind source separation and nonnegative matrix decomposition)

车辆检测追踪显示车辆，计算车辆的车流量，判断车辆的位置信息(Vehicle testing track)

This toolbox provides routines for working with multiwavelets (which includes scalar wavelets as a special

模糊C-均值算法容易收敛于局部极小点，为了克服该缺点，将遗传算法应用于模糊C-均值算法(FCM)的优化计算中，由遗传算法得到初始聚类中心，再使用标准的模糊C-均值聚类算法得到最终的分类结果。(Fuzzy C- means algorithm is easy to converge to a local minimum point, in order to overcome this drawback, the genetic algorithm is applied to fuzzy C- means algorithm (FCM) optimization calculations by the genetic algorithm initial cluster centers, and then using standard fuzzy C- means clustering algorithm to obtain the final classification results.)

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.)