Hi, I have a question about Gröbner bases and using the Rosenfeld_Grobner algorithm in diffalg. What is best to use? If the equations only contain time differentiated variables, is it better to differentiate the equations "by hand" first and let the Gröbner package deal with the problem or is it better to just plug the whole thing into diffalg from the start?

I'm wondering about the complexity on Gröbner basis. I think I've heard something about O(2^2^n) or something like that. Is that true?

I make som calculations in Maple and I get an output like: diff(y(t),t) = y(t) + u(t) Later I export this to Latex but I'd prefer the shorter notaion with "dots" on the time derivative, i.e. y_dot(t) = y(t) + u(t) Is there a way to get maple to output this?

Hi all, I'm currently using the diffalg package to eliminate unknown signals and use the known ones for diagnosis (fault detection). At the moment, I have generated a lot of smaller equation systems from the large one I'm trying to diagnose. However, I get a lot of equation systems (too many to solve all of them), some goes very quickly to solve, others take a loooong time (too long for my poor computer). My question is, is there a way to "rank" the equation systems so I can start with the ones that have the highest probability to solve (other than the obvious number of equations in them)