Dynamically-Adaptive Winner-Take-All Networks

Unfortunately, convergence of normal WTA networks is extremely sensitive to the magnitudes of their weights, which must be hand-tuned and which generally onlyprovide 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 DAWTA regulatory unit dynamically adjusts its level of activation during competition to provide the right amount of inhibition to differentiate betweencompetitors and drive a single winner. This dynamic adaptation allows DAWTA networks to perform the winner-lake-all function for nearly any network size or initial condition.