The-main-MATLAB-command-summary

现有的几个网络拓扑随机发生器，其实很难生成理想的网络拓扑结构，其主要原因在于很难控制节点的疏密和间距。我们提出来的这个改进算法，在随机抛撒节点的时候使用了K均值聚类，由本算法作为网络拓扑发生器，网络节点分布均匀且疏密得当，边的分布也比较均衡(The few existing random network topology generator, is in fact very difficult to generate the desired network topology, the main reason it is difficult to control the node density and spacing. We put forward the improved algorithm, throw in random nodes when using the K-means clustering, by the algorithm as a network topology generator, network nodes and spacing evenly distributed properly, the edge of a more balanced distribution of)

函数的界面函数和一些控件的函数的使用等等，帮助用户使用matlab并很方便的理解(Function of the interface functions and the use of some of the control functions, etc., and to help users easily understand the matlab)

利用matlab编程实现gvf snake算法，并得到了较好的结果，比传统的snake有较大的改进(using Matlab programming gvf snake algorithm, and a better result, than the traditional snake a greater improvement)

雷克子波的时域波形，在地震信号分析中是一个常见的处理信号。(Ricker wave time domain waveform, a common processing signals in seismic signal analysis.)

布谷鸟搜索算法[CuckooSearch（CS）],也叫杜鹃搜索,是由剑桥大学Xin-SheYang(杨新社)教授和S.Deb于2009年提出的一种新兴启发算法CS算法通过模拟某些种属布谷鸟(CuckooSpecies)的寄生育雏(BroodParasitism)来有效地求解最优化问题的算法.同时，CS也采用相关的Levy飞行搜索机制。(Cuckoo search algorithm [CuckooSearch (CS)], also called cuckoo search algorithm is a new heuristic algorithm CS by Cambridge Xin-SheYang (Yang Novosti) professors and S.Deb proposed in 2009 by simulating some species of cuckoo Bird (CuckooSpecies) parasitic brood (BroodParasitism) effectively algorithm optimization problem. At the same time, CS also uses associated Levy flight search mechanism.)

Temperature Dependence of the concentration n electrons in the conduction band of n type semiconductor.

此代码为一个目标跟踪程序，直接运行程序即可，此外还有其他参数的显示(This code for a target tracking program, you can run the program directly, in addition to the display of other parameters)

modele of floutp you can utise thise simulion ofn to gett the correct value

This is a matlab code for cropping the local parts(left eye,right eye,nose,mouth)

Some algorithms of variable step size LMS adaptive filtering are studied．The VS—LMS algorithm is improved． Another new non-linear function between肛and e(／ t)is established．The theoretic analysis and computer simulation results show that this algorithm converges more quickly than the origina1．Furthermore，better antinoise property is exhibited under Low—SNR environment than the original one．(variable step size of a LMS daptive filtering are studied. The VS-LMS algorithm is improved. Another new non-linear function between anus and e (/ t) is established. The theoretic analysis and computer simulatio n results show that this algorithm converges mo 're quickly than the origina1. Furthermore, better antinoise property is exhibited under L ow- SNR environment than the original one.)