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

聯(lián)想記憶

Foreknowledge

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

FIR

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.

glisten

Blood-Clot

長處

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

匍匐

不感興趣

夾克怕包裹

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

使更活躍

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