NEURAL COOPERATING PROCEDURE FOR FRACTAL ANALYSIS OF ARTIFICIAL DRAWINGS

We assess a procedure for discovering the mixing ratios of transformat ions within the bench of affine maps of a probabilistic iterated fuzzy functions system which gives rise to 256 artificial color drawings. A first hypothesis on these ratios is obtained from a pseudo-ergodic es timate of the probabilities of matching special paths during the image generation. The job of the neural network is to remove biases from th is hypothesis after a proper training. The reconstructed images are ne arly identical to their original ones also on instances not used to tr ain the network, and their representation through the above ratios att ains a very high compression rate.