Are the RLS filter and Kalman filter gradient methods? I would like to extend my previous question
What is difference between LMS and gradient-descent adaptation?
with this other question.

I found out, that RLS and Kalman filter learning seems to be somehow similar. My question is: Can be those algorithms called gradient descent methods? If not, how is this kind of algorithms called?
Recursive least squares (RLS) filters don't use gradient descent. As their name suggests, they use a least-squares fit to determine the optimum coefficients at each time step. Via clever formulation of the filter structure, one can use the calculations done from time step $n$ to recursively calculate the updated coefficients for time step $n+1$ without having to do the full least-squares fit again.