Dynamically-Adaptive Winner-Take-All Networks

Unfortunately, convergence of normal WT A networks is extremely sensitive to the magnitudes of their weights, which must be hand-tuned and which generally only provide the right amount of inhibition across a relatively small range of initial conditions. This paper presents Dynamjcally Adaptive Winner-Telke-All (DA WTA) netw rls, which use a regulatory unit to provide the competitive inhibition to the units in the network. The DA WT A regulatory unit dynamically adjusts its level of activation during competition to provide the right amount of inhibition to differentiate between competitors and drive a single winner. This dynamic adaptation allows DA WT A networks to perform the winner-lake-all function for nearly any network size or initial condition.