Competitive learning using competitive activation rules

A description is presented of the first learning rule devised to work with competitive activation mechanisms. Terminology is defined and the idea of a competitive activation mechanism is summarized. A basic unsupervised competitive learning rule for use with competitive activation mechanisms is presented, and the results of a small series of experiments that demonstrate the viability of this approach are described. The basic unsupervised competitive learning rule is then analyzed, identifying fixed points and contrasting its use with competitive and noncompetitive activation rules. Analysis shows that using competitive activation mechanisms corrects for weight vector distortions that have occurred in previous competitive learning systems. Simulations provide evidence that this learning rule can be used effectively