ovsf(spreading_one)

数字PID的matlab仿真程序，针对刘金琨的先进PID控制的matlab仿真，里面的部分程序进行了修改 第三章(Digital PID of matlab simulation program for Liu Jinkun matlab advanced PID control simulation, which part of the program were modified Chapter)

延迟加载的，转发别人的，感觉不错，适合初学者使用的，可以了解下一部加载(Asynchronize of datagrid it fit newer)

通用模拟退火优化算法 General simulated annealing algorithm 模拟退火优化算法能过较大限度的避免局部最优解 (General simulated annealing optimization algorithm General simulated annealing algorithm simulated annealing optimization algorithm can have a greater level of local optimal solution to avoid)

Moment Invariant source code in matlab

给出了用消元法解线性方程组的方法，消元法是解线性方程组有效地方法。(In this paper, the elimination method of solving linear equations, elimination method is effective method of solving linear equations.)

使用matlab做数据分析，里面有ppt和例程。(Analyze data by using MATLAB, which has PPT and routines.)

若不希望用与估计输入信号矢量有关的相关矩阵来加快LMS算法的收敛速度，那么可用变步长方法来缩短其自适应收敛过程，其中一个主要的方法是归一化LMS算法（NLMS算法），变步长 的更新公式可写成 W（n+1）=w（n）+ e（n）x（n） =w（n）+ （3.1） 式中， = e（n）x（n）表示滤波权矢量迭代更新的调整量。为了达到快速收敛的目的，必须合适的选择变步长 的值，一个可能策略是尽可能多地减少瞬时平方误差，即用瞬时平方误差作为均方误差的MSE简单估计，这也是LMS算法的基本思想。 (Want to estimate if the input signal vector and the relevant matrix to speed up the convergence rate of LMS algorithm, then the variable step size method can be used to shorten its adaptive convergence process, one of the main method is normalized LMS algorithm (NLMS algorithm) , variable step-size update formula can be written W (n+ 1) = w (n)+ e (n) x (n) = w (n)+ (3.1) where, = e (n) x (n) the right to express filter update vector iterative adjust the volume. In order to achieve the purpose of fast convergence, we must choose the appropriate value of variable step size, a possible strategy is as much as possible to reduce the instantaneous squared error, which uses the instantaneous squared error as the mean square error MSE of the simple estimate, which is the basic LMS algorithm思想.)

Genetic_Ant_Algorith - 蚁群遗传算法的实现，VC++源代码！蚁 群遗传算法的实现，VC++源代码！蚁群遗传算法的实现，VC++源代码！-Ant Colony Genetic Algorithm, (Ant Colony Genetic AlgorAnt Colony Genetic Algorithmithm)

绘分形树：tree(n,a,b),n为分形树迭代次数 a,b为分枝与竖直方向夹角 (Painted fractal tree)

为了有效地应用遗传算法解决 鲁棒控制系统设计问题，将遗传算法与局部优化方法相结合，提出了基于降维扫描方法的自适应多目标遗传算法（DRSA-MOGA）。通过引入适应度函数标准化方法、基于最优Pareto解集搜索的降维扫描方法和适应度函数自适应调整方法，提高了算法的全局优化性能和局部搜索能力。仿真结果表明，DRSA-MOGA算法在不损失解的均匀度的情况下可以达到很高的逼近度(For effective application of genetic algorithms to solve robust control system design problems, genetic algorithms and local optimization method, based on reduced-order adaptive scanning method multi-objective genetic algorithm (DRSA-MOGA). Fitness function through the introduction of standardized methods, based on the Pareto optimal solution set of search methods and dimensionality reduction scan fitness function adaptive adjustment method, the algorithm improve the performance of global optimization and local search capabilities. The simulation results show that, DRSA-MOGA algorithm solution without loss of uniformity can be achieved under a high degree of approximation)