Associative memory of gray-scale images based on chaotic neural networks

We propose a novel correlative learning rule for multi-value patterns, considering that conventional associative memory system processes only binary ones. Successful memory and recognition were achieved on the bases of a modified globally coupled map model (S-GCM) with the proposed method. An analysis of the recognition results and factors are also given.