KF_and_EKF_standard

用matlab编写的，进行视频镜头的分割(Using matlab prepared video footage of the partition)

group face detection

在BA无标度网络中求平均传递时间算法的matlab原程序。用该算法可以计算出网络拥塞的临界点。 (In the BA scale-free network in order to pass the time on average algorithm matlab original procedure. The algorithm can be used to calculate the critical point of network congestion.)

These programs are used to calcualted a Duel phase lag model with different methods.

this program is to zoom the given image. you provide the image. it will zoom it

ICS课程archlab Partb 作业提交包（纯手工制作）(ICS courses archlab Partb job submission package (handmade))

matlab cod for array processing music code

计算LP01模式分布，对于光学的传输模式的把握和分析能器到很大的作用(Calculate the distribution of LP01 mode, the transmission mode for the optical analysis can grasp and very useful device to)

一个双原子分子的势能函数为 Ep=E0[(r0 )12-2(r0/r)6] 式中，ｒ为两原子间的距离。ａ.绘制势能曲线。b.由图说明r0是势能最小的分子间距。c.由图说明E0是分子势能的最小值。 (A diatomic molecule potential energy function for the Ep = E0 [(r0 r) 12-2 (r0/r) 6] where, r is the distance between two atoms. a. draw the potential energy curve. b. r0 is the potential energy by the figure shows the minimum distance between the molecules. c. Figure shows the molecular potential energy E0 is the minimum.)

说明：  遗传算法（Genetic Algorithm，GA）最早是由美国的 John holland于20世纪70年代提出,该算法是根据大自然中生物体进化规律而设计提出的。是模拟达尔文生物进化论的自然选择和遗传学机理的生物进化过程的计算模型，是一种通过模拟自然进化过程搜索最优解的方法。该算法通过数学的方式,利用计算机仿真运算,将问题的求解过程转换成类似生物进化中的染色体基因的交叉、变异等过程。在求解较为复杂的组合优化问题时,相对一些常规的优化算法,通常能够较快地获得较好的优化结果。遗传算法已被人们广泛地应用于组合优化、机器学习、信号处理、自适应控制和人工生命等领域。(Genetic algorithm (GA) was first proposed by John Holland of the United States in the 1970s. It is designed and proposed according to the evolution law of organisms in nature. It is a computational model of biological evolution process simulating natural selection and genetic mechanism of Darwin's biological evolution theory. It is a method to search the optimal solution by simulating natural evolution process. The algorithm transforms the solving process of the problem into a process similar to the crossover and mutation of chromosome genes in biological evolution by means of mathematical method and computer simulation. When solving complex combinatorial optimization problems, compared with some conventional optimization algorithms, it usually can get better optimization results quickly. Genetic algorithm has been widely used in combinatorial optimization, machine learning, signal processing, adaptive control and artificial life.)