Find the eigenvalues using the characteristic equation, \(|A-\lambda I|=0\). You will get, \(\lambda=2\pm 3i\). Then for each eigenvalue find the corresponding eigenvectors. The eigenvectors for a given eigenvalue define the eigenspace for that particular eigenvalue. Finally find a basis for each eigenspace.
Some worked examples similar to your problem can be found here. Hope you can continue.
Are there known conditions under which a Markov Chain is also a Martingale? I know only that the only Random Walk that is a Martingale is the symmetric one, i.e., p= 1-p =1/2.
Hello !
I derived equations of stress tensor 2D transformation.
Some details: I have plane ABCD in two cases (see top on the pic) and I know tensor components for case 1 only. Only plane ABCD rotate in two cases (top of the picture) but not coordinate system. Coordinate system rotates only on the bottom of picture.
I want to obtain expression that connects tensor for case 1 and tensor for case 2.
My attempt:
Are these equations correct? Is there more easier expression for stress tensor...