Neural module for real-time simultaneous discrimination and locking on different temporal series in noisy environment

After a short discussion on the problems related to the higher order correlations treatment in Hopfield neural net, we propose a modified architecture able to rearrange dynamically its topology in function of the input representation. The relations of this problem with computability problems are briefly considered, particularly in view of avoiding exponential time in computation. Some experimental results are shown for the recognition of particle traces in high energy accelerators and in speaker independent speed recognition.