channel_matrix-V1

matlab simulink LQR仿真(LQR simulation by simulink of Matlab)

i like electronic, i share this file to anyone. i hope it help anyone to interface.

Matlab toolbox neural network function neural network 06b AIDS on neural network toolbox

人工鱼群算法，在一片水域中,鱼往往能自行或尾随其他鱼找到营养物质多的地方,因而鱼生存数目最多的地方一般就是本水域中营养物质最多的地方，人工鱼群算法就是根据这一特点,通过构造人工鱼来模仿鱼群的觅食!聚群及追尾行为,从而实现寻优，以下是鱼的几种典型行为:(1)觅食行为:一般情况下鱼在水中随机地自由游动,当发现食物时,则会向食物逐渐增多的方向快速游去。(2)聚群行为:鱼在游动过程中为了保证自身的生存和躲避危害会自然地聚集成群，鱼聚群时所遵守的规则有三条:分隔规则:尽量避免与临近伙伴过于拥挤 对准规则:尽量与临近伙伴的平均方向一致 内聚规则:尽量朝临近伙伴的中心移动。(3)追尾行为:当鱼群中的一条或几条鱼发现食物时,其临近的伙伴会尾随其快速到达食物点。特点：1)具有较快的收敛速度,可以用于解决有实时性要求的问题 2)对于一些精度要求不高的场合,可以用它快速的得到一个可行解 3)不需要问题的严格机理模型,甚至不需要问题的精确描述,这使得它的应用范围得以延伸.停止条件1) 判断连续多次所得的均方差小于语允许的误差2）判断某个区域的人工鱼群的数目达到某个比率3）联系多次所获取的值均不能超过已寻找的极值。 (Artificial fish swarm algorithm, in the midst of the waters, the fish tend to own or trailing other fish to find places with more nutrients and thus the largest number of fish survival in general is a place where most of the nutrients in the waters, artificial fish swarm algorithm is based on thisa characteristics, by constructing artificial fish to mimic fish foraging clusters and rear-end behavior, in order to achieve optimization, several typical behavior of the fish: (1) foraging behavior: the general case of fish in the water at randomthe free-swimming, swimming quickly when food is found, then the food is gradually increasing in the direction. (2) cluster behavior: the fish swimming in the process of naturally clustered, and abide by the rules when the fish cluster there are three: separate rule: try to avoid overcrowding with neighboring partners in order to ensure their own survival and to avoid harm alignment rules: as far as possible consistent with the mean direction of the)

matalab 实验案例 c++ 积分(matlab you can use it for your maths)

Stable adaptive fuzzy control for MIMO non linear systems 2011

说明：  该程序通过模仿生物的遗传特点，解决全局最优解的问题(The program solves the problem of global optimal solution by imitating the genetic characteristics of organisms)

The mobile robot has to find the optimal path which reduces the number of steps to be taken between the starting point and the target ending point. GAs can overcome many problems encountered by traditional search techniques such as the gradient based methods. The proposed controlling algorithm allows four-neighbor movements, so that path-planning can adapt with complicated search spaces with

a sliding P ID mode controller with P ID sliding surface is p resented. Lyapunov stability theory was utilized to achieve the stability analysis. And while there exists uncertainty in satellite inertia parameters or external disturbance

garch-copula-VaR模型用于计算投资组合风险(garch-copula-VaR model is used to calculate portfolio risk)