The stability of the analog Hopfield neural network with iterative dynamics

We first present an example which shows that a general dynamic system with an infinite number of fixed points may never stabilize, even when there exists a Lyapunov function which strictly decreases along all possible trajectories. We then explain why the analog Hopfield neural network with iterative dynamics always converges to a fixed point, regardless of how many fixed points it has.