Neural networks : iterative unlearning algorithm converging to the projector rule matrix
A. Yu. Plakhov, S. A. Semenov · Journal de Physique I · 1994
The iterative unlearning algorithm for connectivity self-correction is proposed. No presentation of patterns during the iteration process is required. Starting from the Hebbian connectivity, the convergence of the (rescaled) iterated connection matrix to the projector rule one is proven, for arbitrary set of p < N binary patterns.