Titlebook: Neural Nets WIRN VIETRI-97; Proceedings of the 9 Maria Marinaro,Roberto Tagliaferri Conference proceedings 1998 Springer-Verlag London Limi

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Employment of a Progressive Learning Neural Network for Identification and Controlecause of its inherent capacity of learning on-line. ..After describing the PLN, the generalised and specialised inverse control schemes are introduced and then a method for using the PLN in this kind of control is shown. In particular a new version of this PLN is developed for the on-line control w

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What Size Needs Testing?capability of a neural network generally demands smaller sample size than training it..We move in an extended PAC learning framework and use some recent results in terms of sentry functions of a concept class to statistically proof our claims.

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Sequences of Discrete Hopfield’s Networks for the Maximum Clique Problemthat, in polynomial time, converge to a state representing a clique for a given graph. Some experiments made on the DIMACS benchmark show that the approximated solutions found are promising. Finally, the possibility to extend this technique to other .-hard problems and to implement it onto neural ha

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A Distribution-Free VC-Dimension-Based Performance Boundd the target binary function is larger than ε and the empirical error on the examples is smaller than a fixed not-null fraction of ε. The given bounds are independent of the probability distribution on the input space and improve some existing results on generalization abilities of an adaptive binar

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Attractor Neural Networks as Models of Semantic Memoryn order to model human semantic memory operation. Our simulations show that this model is able to reproduce a particular quantitative feature of this operation observed in experiments with human subjects, i.e. the correlation between high values of the prototypicity of exemplars of a given concept a