relation: http://eprints.imtlucca.it/1693/
title: Computationally Efficient Approximation Schemes for Functional Optimization
creator: Alessandri, Angelo
creator: Gnecco, Giorgio
creator: Sanguineti, Marcello
subject: QA75 Electronic computers. Computer science
description: Approximation schemes for functional optimization problems with admissible solutions dependent on a large number d of variables are investigated. Suboptimal solutions  are considered, expressed as linear combinations of n-tuples from a basis set. The uses of fixed-basis and variable-basis approximation are compared. In the latter,  simple computational units with adjustable parameters are exploited. Conditions are discussed, under which the number n of basis functions required to guarantee a desired accuracy does not grow “fast” with the number d of variables in admissible solutions, thus mitigating the “curse of dimensionality”. As an example of application,  an optimization-based approach to fault diagnosis for nonlinear stochastic systems is presented. Numerical results for a complex instance of the fault-diagnosis problem are given. 
publisher: Nova Publishers
date: 2008
type: Article
type: PeerReviewed
identifier:   Alessandri, Angelo and Gnecco, Giorgio and Sanguineti, Marcello  Computationally Efficient Approximation Schemes for Functional Optimization.  International Journal of Computer Research, 17 (1/2).  pp. 153-189.  ISSN 1535-6698      (2008)  
relation: https://www.novapublishers.com/catalog/product_info.php?products_id=20971