mp_code

注水定理 干扰信道 MIMO 运用迭代的方法求得最佳信道容量(MIMO interference channel)

LM算法的MATLAB实现。Levenberg-Marquardt算法是最优化算法中的一种。最优化是寻找使得函数值最小的参数向量。(LM algorithm in MATLAB. Levenberg-Marquardt algorithm is an optimization algorithm. Optimization is to find the minimum value makes the function parameter vector.)

阵列信号处理 各种经典算法 MUSIC ESPRIT等 值得珍藏(Array signal processing algorithms blessed with a variety of classic)

这是matlab的遗传算法工具箱，在matlab的环境下使用，用于求解多目标优化问题(This is a matlab genetic algorithm toolbox in matlab environment used for solving multi-objective optimization problem)

该程序是IEEE118节点系统的节点导纳矩阵求取程序，输入相应的已知参数便可得到。(The program is a nodal admittance matrix IEEE118 bus system to strike the program, enter the corresponding known parameters can be obtained.)

Matlab中使用动态规划解决数学建模中的花瓶问题，即有限制条件的寻优过程(Applied Dynamic programming to solve the problem of bottles)

用matlab仿真模拟骑车功能，左右转向，油门，历程功能。(Simulation ride, about steering, throttle, the course features)

对通信系统中的注水算法技术进行matlab仿真。(The water injection system of communication technology matlab simulation algorithm.)

蕞优分组周游路线问题是一类物流智能调度问题，是众多的计算难度极大的组合爆炸问题之一。自从运输问题最早是由Hitchcock在1941年提出的[2][4]后，人们对这一类问题给予了极大的关注并进行了大量的研究，提出了有效解决问题的优化算法——单纯形法的变形[2]。但由于问题规模的扩大，纯数学方法在允许的时间和空间上都很难找到问题的最优解，于是人们开始转向寻找问题的近似最优解，遗传算法以其在求解最优化问题中的独特的自组织性、自适应性很快进入人们的视野。 经典的遗传算法对于求解多目标的NP完全性问题非常有效，但对于有多个限制条件的多目标最优化问题缺显得有点力不从心，很难得到稳定度较高、收敛较快的解。本文提出的双层遗传算法模型给这一类问题提供了一个很好的解决方法，虽然建模条件限制了描述的问题的通用性，有待推广，但它能有效利用问题的领域知识，提高了求解效率，保证了解的可行性和最优性，算法思想极具推广潜力，可在其它物流智能调度问题求解算法设计中借鉴。(The most optimal packet travel route problem is a kind of intelligent logistic scheduling problem is one of combinatorial calculation difficult problem many. Since the transportation problem was first proposed by Hitchcock in 1941 after the [2][4], the people of this class of problems given great attention and made a lot of research, the deformation of [2] optimization, simplex method algorithm is effective to solve the problem of. But due to the expansion of the scale of the problem, the pure mathematical methods in the allowed time and space are very difficult to find the optimal solution of the problem, so people begin to turn to the approximate optimal solution for the problem, genetic algorithm in solving optimization problems with its unique in the self-organizing, adaptive soon entered people s field of vision. Very effective classical genetic algorithm for solving multi-objective NP complete problems, but for the multi-objective optimization problem with multiple constraints. I)

matlab传染病sis及相关模型的图的模型，及运用(Matlab infectious disease sis and related model diagram model, and application)