逆矩阵的奇异性 [英] Singularity for inverse matrix

问题描述

作为数据，我得到一个矩阵A，但是在我的算法中，我需要对其求逆.我要做的是:

As data I get a matrix A but in my algorithm I need to work on its inverse. What I do is:

C = inv(A) + B;

然后在另一行中更新A.在接下来的循环中，对于该算法，我同样需要(更新)逆.等等.在以后的周期中，我得到以下信息:

Then in another line I update A. In the next cycles I also need (updated) A inverse, again for this algorithm. And so on. In the later cycles I get this:

Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND = 1.425117e-019

或者这个:

Warning: Matrix is singular to working precision.

或者这个:

Warning: Matrix is singular, close to singular or badly scaled. Results may be inaccurate. RCOND = NaN.

您能帮我如何避免这种奇异之处吗?矩阵总是平方的.

Can you help me how to avoid such singularity? Matrix is squared always.

推荐答案

您可以向A添加一些分钟身份矩阵:

You can add some minute identity matrix to A:

A = A + small_coeff * eye(size(A));

以使所得矩阵足够非奇异

so that resulting matrix will be sufficiently non-singular

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