maofing_v60

说明：  通信系统的仿真,Viterbi译码可用于卷积码等的译码解决方案,可以用于通信领域,本例子给出了基于matlab的程序,可用于实际的仿真!(communications system simulation, Viterbi decoder can be used as a convolutional code decoding solution, communications can be used, the example is given of the procedures based on Matlab can be used for actual simulation!)

虚拟技术 ----ｖｍ　ｗａｒｅ　实验教程(virtual technology-vm ware experimental Guide)

matlab 遗传算法GA，粒子群算法PSO,蚁群算法AS 前段时间上智能计算方法实验课上，自己做的程序。帖到这里，希望有人能改进它们，交流经验这样更有价值。 遗传算法解决最小生成树问题，PURFER编码。 粒子群算法做无约束最优化问题。 蚁群算法解决TSP问题。 如果有宝贵经验希望能交流一下，谢谢，呵呵(matlab genetic algorithm GA, particle swarm optimization PSO, ant colony algorithm for calculation of AS some time ago on the intelligent test classes, make their own procedures. Quote here, hope someone can improve them, and exchange of experience which is more valuable. Genetic algorithm to solve the minimum spanning tree problem, PURFER coding. Particle swarm optimization to do unconstrained optimization problem. Ant colony algorithm to solve the TSP problem. If there is hope to exchange our experience, thank you, He He)

Norden E. Huang写的关于HHT变换的介绍及其相关问题(Norden E. Huang Transform to write an introduction on the HHT and related issues)

多种数学建模方法算法代码，每年数学建模代码(A variety of mathematical modeling algorithm code, annual mathematical modeling code)

可变聚类无标度网络源代码。提高了BA网络的聚类系数。(Variable clustering scale-free network source code. Improve the clustering coefficient of BA networks.)

AIC 系统辨识算法matlab原程序 供大家参考(AIC system identification algorithm matlab program for your reference the original)

卡拉曼滤波 用于目标跟踪 老师写的例子程序 效果不错 (Karaman filtering for target tracking teacher wrote a good example of program effects)

统的联合概率数据关联算法(IPDA)是在密集杂波环境下的一种良好的多目标跟踪算法， 但它是针对单传感嚣对多目标跟踪的情况下使用，不能直接用于多传感器对多目标的跟踪。针对这 一问题，文中提出了一种适用于多传感器多目标跟踪的JPDA算法，它以极大似然估计完成对来自 多传感器的测量集合进行同源最优分划，然后采用JPDA方法对多目标进行跟踪。经过理论分析和 仿真试验，证明了该方法能有效地进行多传感器多目标的跟踪，且具有算法简单、跟踪精度高、附 加的计算量小等优点。(Abstract)m JointProbabilisticDataAssociation(JPDA)solves single sensormultitatgcttrackingin ClUtter,butitc锄not bc used directly in mnitisensor multitarget tracking．喇8 paper presents a method to implement multi—sensor multi—target tracking by combining maximum likelihood estimation wim JPDA The maximum Iikelihood estimation is used to classify the same source observations at one time into the same set,and血en JPDA implements multi—target uacking after the position fitsed．The theory analysis and computer simulation show that this algorithm may achieve multi—sensor multi—target tracking perfectly with low calculation load added and higher precision 。)

神经网络修改BP辨识算法，用于辨识复杂的非线性系统，相对传统BP算法，具有计算快等优点(Modify BP neural network recognition algorithm for identification of complex nonlinear system, compared to the traditional BP algorithm has the advantages of quick calculation)