完整代码，可直接运行

完整代码，可直接运行

粒子群算法的寻优算法-非线性函数极值寻优 matlab程序

python求极值点主要用到scipy库。 1. 首先可先选择一个函数或者拟合一个函数，这里选择拟合数据：np.polyfit import pandas as pd import matplotlib.pyplot as plt import numpy as np from scipy import signal #滤波等 xxx = np.arange(0, 1000) yyy = np.sin(xxx*np.pi/180) z1 = np.polyfit(xxx, yyy, 7) # 用7次多项式拟合 p1 = np.poly1d(z1) #多项式系数 print(p1) # 在屏幕

MATLAB peakfiender matlab极值查找程序 n迭代次数，data是一维输入，peakval是找到峰值，peakcoor是峰值所在位置

根据自然计算课程里面，说的遗传算法自己编的，可用。编码，交叉互换，基因突变，解码过程都有详细的注释。这个是matlab编的，出图也很方便。

本资源为.zip压缩包，内含一元函数求极值的MATLAB源文件。注：源文件中的一元函数需要你自己修改，修改方式为在target.m文件中重新定义你自己的一元函数，且需要在gene.m文件中的boundsbegin变量、boundsend变量重新赋值你所定义的一元函数的上下界。

Given symmetric matrices B,D ∈ R n×n and a symmetric positive definite matrix W ∈ R n×n , maximizingthe sum of the Rayleighquotientx ? Dx andthe gener- alized Rayleigh quotient x ? Bx x ? Wx on the unit sphere not only is of mathematical interest in its own right, but also finds applications in practice. In this paper, we first present a real world application arising from the sparse Fisher discriminant analysis. To tackle this problem, our first effort is to characterize the local and global maxima by investi- gating the optimality conditions. Our results reveal that finding the global solution is closely related with a special extreme nonlinear eigenvalue problem, and in the spe- cial case D = μW (μ > 0), the set of the global solutions is essentially an eigenspace corresponding to the largest eigenvalue of a specially-defined matrix. The characteri- zation of the global solution not only sheds some lights on the maximization problem, but motives a starting point strategy to obtain the global maximizer for any monoton- ically convergent iteration. Our second part then realizes the Riemannian trust-region method of Absil, Baker and Gallivan (Found. Comput. Math. 7:303–330, 2007) into a practical algorithm to solve this problem, which enjoys the nice convergence prop- erties: global convergence and local superlinear convergence. Preliminary numerical tests are carried out and empirical evaluation of its performance is reported.

通过采用遗传算法实现函数全局最优的极值计算。采用matlab语言编写完成，可以直接运行，包含图形的绘制

霍姆斯（JW Holmes）提出了广义极值（GEV）分布的介绍，并在他的书“结构的风荷载” [1]中应用了极风速度。 本子程序复制了[1]中给出的一些示例，带有和不带有Matlab统计工具箱[2]。 本呈件包含： •2个函数fitGEV.m和mygevcdf.m •一个Matlab Livescript文件Documentation.mlx，它再现了[1]中给出的一些结果。 •一个数据文件文件EastSale.mat 参考： [1] Holmes，JD（2015）。 结构的风荷载。 CRC出版社。 [2] https://www.mathworks.com/products/statistics.html