An Analysis of the Application of B-spline Neurofuzzy Construction Algorithms
Brown, M., Bossley, K.M. and Harris, C.J. (1996) An Analysis of the Application of B-spline Neurofuzzy Construction Algorithms. EUFIT '96 , 1830--1834.
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This paper investigates the application of the B-spline neurofuzzy construction algorithms, developed by the ISIS research group, to identifying appropriate models from two standard data sets. The two data sets are the Box-Jenkins data and a simulated system data set, both of which can are described by discrete time series models. It is shown that the construction algorithms pick out the dominant linear components associated with this data, as well as the small nonlinearities, and the model's structure facilitates the analysis of the data where errors occur. This is simplified by the incorporation of these techniques inside NeuFrame: a PC-based graphical development environment.
|Item Type:||Conference or Workshop Item (UNSPECIFIED)|
|Divisions:||Faculty of Physical and Applied Science > Electronics and Computer Science > Comms, Signal Processing & Control
|Date Deposited:||04 May 1999|
|Last Modified:||02 Mar 2012 12:18|
|Contributors:||Brown, M. (Author)
Bossley, K.M. (Author)
Harris, C.J. (Author)
|Further Information:||Google Scholar|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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