Abstract:
The paper presents a technique for modeling reachable states of positive linear discrete-time systems (PLDS) using static feed-forward neural networks. The proposed metho...Show MoreMetadata
Abstract:
The paper presents a technique for modeling reachable states of positive linear discrete-time systems (PLDS) using static feed-forward neural networks. The proposed method is based on design of self-regulating two layer perceptron type neural network for the modeling of reachable sets of PLDS systems represented by polyhedral cones using a pattern recognition method.
Date of Conference: 08-10 May 2002
Date Added to IEEE Xplore: 07 November 2002
Print ISBN:0-7803-7298-0
Print ISSN: 0743-1619