INFORMATION-STORAGE MATRICES IN NEURAL NETWORKS

A new neural network model with feedback based on the concept of information storage matrices is proposed. This model is similar to the Hopfield and spectral type neural networks but has a more general structure. The presentation gives a fully developed theory for first-order networks, including results on the formation of fixed points and their domains of attraction. These results are used to determine, in deterministic sense, the information storage capacity. The algorithm is applied to the DNA sequencing problem. It is demonstrated how a hidden genetic information in an arbitrary long DNA strand can be extracted. © 1990 Springer-Verlag.