这只是警告，不是报错。实际上，这是在计算矩阵相除时，由于计算出现奇异时发出的警告。rank是矩阵的秩，tol是误差。从你的代码看，确实存在错误。你原本的意思应该是 Z=X.*Y./sqrt(X.*X+Y.*Y)；在这里应该有一个点，这是计算矩阵对应位置元素的除法运算。因为缺少了一个点，所以变成了矩阵除法...
这只是警告，不是报错 实际上是计算矩阵相除的时候，因为计算出现奇异时，发出的警告 rank是矩阵的秩，tol是误差 不过从你的代码看，确实是错了 你的原来意思应该是 z=x.*y./sqrt(x.*x+y.*y);| 这里应该有个点 计算的是矩阵对应位置元素的除法运算 因为缺少了一个.所以变成了矩阵除法 这是最...
arning: Rank deficient, rank = 0, tol = 1.#INFe+000.> In Untitled2 at 2 Warning: ...
Open in MATLAB Online H is a hadamard matrix of order 16. Because i scrambled the signal using frame of 16 samples using: y(:,k) = H*x; k = k + 1; I am now trying to descrambled it using 16 samples too by doing: ori_sig(:,k) = y\H; ...
I have a typical least squares problem, i.e I have to find the value of x that minimizes norm of C∗x(:)−d. C is 180x16 matrix(C is rank deficient,i.e rank(C)=7), x is 4x4 matrix & d is 180x1 vector. However, I have a constraint that rank(x)=1. If x was...
解欠定方程组 A＝[1 -2 1 1;1 -2 1 -1;1 -2 1 5]A= 1 -2 1 1 1 -2 1 -1 1 -2 1 -1 1 -2 1 5 b=[1 -1 5]’x1=A\b Warning:Rank deficient,rank=2 tol=4.6151e-015 x1= 0 -0.0000 0 1.0000 x2=pinv(A)*b x2= 0 -0.0000 0.0000 1.0000 ...
第二算式中0不能作除数，因此取和0差不多的0.000001 clear;clc;L=0.235;x1=0.000001:0.2:2;y1=((0.1*sqrt(2))/pi).*sqrt((1+((0.235/0.1)^2).*((1./x1).^2 ))./((( L+1-L./(x1.^2)).^2)+(0.1^2).*((x1-1./x1).^2)));plot(x1,y1);grid on;...
Since the columns are linearly dependent, the matrix is rank deficient. Specify Rank Tolerance Calculate the rank of a matrix using a tolerance. Create a 4-by-4 diagonal matrix. The diagonal has one small value equal to1e-15. A = [10 0 0 0; 0 25 0 0; 0 0 34 0; 0 0 0 1e...
For rank deficient problems, that is, systems with (numerically) rank deficient coefficient matrix in which a clear gap exists between the large and small singular values, the concept of numerical rank is developed and stable solution methods based on the SVD and rank revealing decomposition are ...
Open in MATLAB Online Ran in: @Sascha Frölich— One possibility is that one or more columns of the design matrix are linearly dependent. ThemeCopy x = randn(5,1); DM = [x x+eps ones(size(x))]; y = randn(5,1); B = DM \ y Warni...