For the modified Hebbian learning rule,
It increases below and decreases above , without crossing that equilibrium. More precisely, for a nonzero initial norm,
Under persistent excitation, meaning the integral tends to infinity, this gives
Without persistent excitation the limiting norm need not reach this value; zero weights remain zero. The quartic norm stabilization of Hebbian learning bounds the norm and supplies negative feedback at large amplitudes.