资源列表
jiashejianyan
- 检验cir模型构造的模型的参数a、b及sigma(Checking the parameters of the model constructed by the CIR model)
蒙特卡罗算法与matlab(精品教程)
- 蒙特卡洛算法也常用于机器学习,特别是强化学习的算法中。一般情况下,针对得到的样本数据集建立相对模糊的模型,通过蒙特卡洛方法对于模型中的参数进行选取,使之于原始数据的残差尽可能的小。从而达到建立模型拟合样本的目的。(Monte Carlo algorithm is also commonly used in machine learning, especially in reinforcement learning algorithm. In general, a relatively fuzzy
拉格朗日插值法_matlab
- 数学最优问题中,拉格朗日乘数法(以数学家约瑟夫·路易斯·拉格朗日命名)是一种寻找变量受一个或多个条件所限制的多元函数的极值的方法。(In the mathematical optimization problem, the Lagrange multiplier method (named by the mathematician Joseph Luis Lagrange) is a method of finding the extremum of a multivariate functio
Particle Swarm Optimization
- 优化算法的一种,粒子群寻优算法。它的基本核心是利用群体中的个体对信息的共享从而使得整个群体的运动在问题求解空间中产生从无序到有序的演化过程,从而获得问题的最优解。(a kind smart mathema algorithm____Particle Swarm Optimization)
dtcwt_toolbox4_3
- 双树复小波(DT-CWT)是传统单小波的推广,该变换具有平移不变性、好的方向选择性和高效的计算效率,因此在图像融合领域较小波更具优势(Double tree complex wavelet (DT-CWT) is a generalization of traditional Dan Xiaobo, which has translation invariance, good direction selectivity and efficient computation efficiency.
DE Algorithm
- DE算法,求最优解,能实现,能运行,是个测试版本,可以在这基础改(Genetic algorithm, the best solution, can be realized, can run, is a test version, can be modified in this basis.)
多目标优化的微分进化算法
- 差分算法,求最优解,能实现,能运行,是个测试版本,可以在这基础改(Genetic algorithm, the best solution, can be realized, can run, is a test version, can be modified in this basis.)
GeneticAlgorithm
- 遗传算法求最优解,能实现,能运行,是个测试版本,可以在这基础改(Genetic algorithm, the best solution, can be realized, can run, is a test version, can be modified in this basis.)
DE-test
- 差分进化算法,求最优解,能实现,能运行,是个测试版本,可以在这基础改(Differential evolution algorithm, to achieve the optimal solution, can be realized, can run, is a test version, can be modified in this basis.)
DeMat
- 差分进化算法,求最优解,能实现,能运行,是个样板(Differential evolution algorithm, the best solution, can be realized, can run, is a template.)
无人机ant-algorithim
- 内容其实就是蚁群算法的路径规划,是三维的,比较粗糙,可以借鉴(The wrong name is actually robot path planning.)
structure dynamic exercise
- 针对随机结构随机激励下的动力响应概率分布求解,基于广义概率密度方法(the calculation of the generalized probability density function)