We have studied the effect of various kinds of damaging that may occur in a neural network whose synaptic bonds have been trained (before damaging) so as to preserve a definite number of patterns. We have used the Hopfield model of the neural network, and applied the Hebbian rule of training...

We introduce a semiempirical theory leading to the ab initio prediction of conducive folding pathways and coarsely resolved native backbone geometries of proteins suddenly exposed to in vitro renaturation conditions. The underlying model incorporates a discrete codification of local steric...

In this paper we present a modification of the strongly diluted Hopfield model in which the dilution scheme, instead of being random, is inspired on biological grounds. We also show that the resulting sparsely connected neural network shows striking features in terms of performance as an...

The pressurizer is one of the critical components in a nuclear reactor, whose main function is to maintain the primary system pressure within specific boundaries. The pressurizer is a large vessel that is made of carbon or low‐alloy steel shell, clad internally with a layer of stainless steel....

We introduce a method for dynamic classification of vector time series data into different regimes. A hidden Markov regime-switching model is used in classification. Past regimes are determined in advance and characterized by first and second moments of the observation vector. In estimation and...