Code Analyzer: INV is slow and inaccurate

Question

When I try to calculate a matrix inverse using Matlab\'s inv() operation:

A = rand(10,10);
b = rand(10,1);

C = inv(A);
D = C*b;

I get the foll

Answer 1

You should listen to Matlab and use the second option. inv(A)*b and A\b are computed with different algorithms under the hood, and \ is indeed more accurate.

The documentation for inv states:

In practice, it is seldom necessary to form the explicit inverse of a matrix. A frequent misuse of inv arises when solving the system of linear equations Ax = b. One way to solve this is with x = inv(A)*b. A better way, from both an execution time and numerical accuracy standpoint, is to use the matrix division operator x = A\b. This produces the solution using Gaussian elimination, without forming the inverse. See mldivide () for further information.

Answer 2

Some additional information:

If you are to calculate

Ax = b

For many different b's, but with a constant A, you might want to pre-factorize A. That is:

[L U P] = lu(A);
x = (U \ (L \ ( P * b)));

Don't know about other fields, but this occurs frequently in power system engineering at least.

Answer 3

If you absolutely need the inverse later on, then you have to compute it. If you can use the backslash operator (\) instead of an inverse again later on, I would stay away from the inverse and listen to MATLAB's suggestion. For numerical reasons, it is always better to use a slash operator when you can, so the second approach is better even though it is slower.