Learning in competitively inhibited neural nets
The competitively inhibited neural network (CINN) is a competitive learning paradigm which is modeled by a collection of ordinary differential equations. A sliding threshold condition has been derived for determining the activity of a CINN neuron. This condition allows the development of a mathematical model for CINN learning. The model is a nonlinear diffusion equation whose solution quantitatively characterizes the learning process. Simulation experiments have validated this model