正在学习无约束共轭梯度方法希望大家一起讨论！

Code demo for single-pixel imaging (SPI) with different reconstruction methods including [1] differential ghost imaging (DGI) [2] gradient descent (GD) [3] conjugate gradient descent (CGD) [4] Poisson maximum likelihood (Poisson) [5] alternating projection (AP) [6] sparse representation compressive sensing (Sparse) [7] total variation compressive sensing (TV)

采用matlab语言编写，用于求解无约束最优化问题

基于CUDA平台GPU加速的共轭梯度法求解器。示例中提供了线性方程组。

共轭梯度法matlab程序 function x = cg(A,b) tol=1e-10; r = b + A*b; w = -r; z = A*w; s = w'*z; t = (r'*w)/s; x = -b + t*w; for k = 1:numel(b); r = r - t*z; if( norm(r) < tol ) return; end B = (r'*z)/s; w = -r + B*w; z = A*w; s = w'*z; t = (r'*w)/s; x = x + t*w; end

预处理共轭梯度法求线性方程组Ax=b的解，数值计算，求解方程

无约束最优化问题典型算法的MATLAB代码

应用该代码进行优化时，首先应将matlab的路径设置至该文件夹的子目录下，然后输入初值，输入函数，点击回车，即可求解

共轭梯度法c++程序，也有黄金分割法和进退搜索法，可以使用，有介绍。/*以下是进退法搜索区间源程序*/ void sb(double *a,double *b,double x[],double p[]) { double t0,t1,t,h,alpha,f0,f1; int k=0; t0=2.5; /*初始值*/ h=1; /*初始步长*/ alpha=2; /*加步系数*/ f0=f(x,p,t0); t1=t0+h; f1=f(x,p,t1); while(1) { if(f1

2019-12-21 19:24:32 30KB 共轭梯度法

1