This is for self-study of N-dimensional system of linear homogeneous ordinary differential equations of the form:
dx/dt=Ax
where A is the coefficient matrix of the system.
I have learned that you can check for stability by determining if the real parts of all the eigenvalues of A are negative. You can check for oscillations if there are any purely imaginary eigenvalues of A.
The author in the book I'm reading then introduces the Routh-Hurwitz criterion for detecting stability and oscillations of the system. This seems to be a more efficient computational short-cut than calculating eigenvalues.
What are the advantages of using Routh-Hurwitz criteria for stability and oscillations, when you can just find the eigenvalues quickly nowadays? For instance, will it be useful when I start to study nonlinear dynamics? Is there some additional use that I am completely missing?
Wikipedia entry on RH stability analysis has stuff about control systems, and ends up with a lot of equations in the s-domain (Laplace transforms), but for my applications I will be staying in the time-domain for the most part, and just focusing fairly narrowly on stability and oscillations in linear (or linearized) systems.
My motivation: it seems easy to calculate eigenvalues on my computer, and the Routh-Hurwitz criterion comes off as sort of anachronistic, the sort of thing that might save me a lot of time if I were doing this by hand, but not very helpful for doing analysis of small-fry systems via Matlab.
Edit: I've asked this at Math Exchange, which seems more appropriate: https://math.stackexchange.com/questions/690634/use-of-routh-hurwitz-if-you-have-the-eigenvalues There is an accepted answer there.