Comparison BAM and discrete Hopfield networks with CPN for processing of noisy data

In the paper we compared three neural networks -Koskopsilas the bidirectional associative memory (BAM) and the discrete Hopfield network (DHN) with the counter propagation network (CPN) for processing of noisy data. We probe into their commonness and distinctness. The experimental results show that de-noise results of three neural networks for weak noise are almost same. BAM of the gradient-descent algorithm is the best for de-noisy processing, at some condition Koskopsilas BAM network is of the same performance as the discrete Hopfield network which is better than the CPN for strong noise.