Stability of the generalised lotto-type competitive learning
Anson M. Y. Luk, Sandra Lien · 2003
Introduces a generalised idea of a lotto-type competitive learning (LTCL) algorithm where one or more winners exist. The winners are divided into tiers, with each tier being rewarded differently. Again, the losers are all penalised equally. A set of dynamic LTCL equations is then introduced to assist the study of the stability of the generalised LTCL. It is shown that if a K-orthant exists in the LTCL's state space, which is an attracting invariant set of the network's flow, it will converge to a fixed point.