小编pr0*_*amR的帖子

我在MATLAB中编码QR分解算法,只是为了确保我的机制正确.这是main函数的代码:

    function [Q,R] = QRgivens(A)
        n = length(A(:,1));
        Q = eye(n);
        R = A;

        for j = 1:(n-1)
            for i = n:(-1):(j+1)
                G = eye(n);
                [c,s] = GivensRotation( A(i-1,j),A(i,j) );
                G(i-1,(i-1):i) = [c s];
                G(i,(i-1):i)   = [-s c];
                Q = Q*G';
                R = G*R;
            end
        end
    end

子函数GivensRotation如下:

    function [c,s] = GivensRotation(a,b)
        if b == 0
            c = 1;
            s = 0;
        else
            if abs(b) > abs(a)
                r = -a / b;
                s = 1 / sqrt(1 + r^2);
                c …

我在 Fortran 95 中编写了一个基本算法，使用通过称为理查森外推法的过程增强的中心差来计算函数的梯度（代码中规定了一个示例）。

function f(n,x)
! The scalar multivariable function to be differentiated

integer :: n
real(kind = kind(1d0)) :: x(n), f

f = x(1)**5.d0 + cos(x(2)) + log(x(3)) - sqrt(x(4))

end function f
!=====!
!=====!
!=====!

program gradient
!==============================================================================!
! Calculates the gradient of the scalar function f at x=0using a finite        !
! difference approximation, with a low order Richardson extrapolation.         !
!==============================================================================!

parameter (n = 4, M = 25)
real(kind = kind(1d0)) :: x(n), xhup(n), xhdown(n), …