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Adaptive model structures for nonlinear system identification

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Dydyński A.

2008

tom Vol. 34, no 2

35-41

This article addresses nonlinear black-box identification using parametric models. A novel adaptive method for the choice of both the model structure and its parameter values is introduced. Experiments in nonlinear time-series modelling and prediction are presented. The method can be seen as unification model of neural networks of all types in the sense as meta-learning applies to the area of predictive data mining, to combine the predictions from multiple models.

Natural Frames and Self-dual Logics

100%

Jennings R. E.

2001

tom Vol. 48, nr 2,3

227-236

The paper revisits a class of model structures introduced by the author in 1974, with particular attention to the system SCon, which axiomatizes the universal class. SCon, which independently deserves notice as an algebraically plausible weakest modal system, is self-dual; that is, its \square and \lozenge have the same logic. The paper gives a semantic analysis of the system on model structures capable of an axiological interpretation, presenting a number of determination- and correspondence-theoretic results. Some intriguing consequences of self-duality for the axiological interpretation of natural frames are discussed.