Ahmad, Robiah and Jamaluddin, Hishamuddin (2002) Radial basis function (RBF) for non-linear dynamic system identification. Jurnal Teknologi A (36A). pp. 39-54. ISSN 0127-9696
Official URL: http://www.penerbit.utm.my/onlinejournal/36/A/JT36...
One of the key problem in system identification is finding a suitable model structure. In this paper, radial basis function (RBF) network using various basis functions are trained to represent discrete-time nonlinear dynamic systems and the results are compared. The orthogonal least squarealgorithm is employed to select parsimonious RBF models. To demonstrate the identification procedure two examples of modelling on linear system were included.
|Uncontrolled Keywords:||radial basis function, system identification, non-linear system modelling, orthogonal least, square algorithm|
|Subjects:||T Technology > TJ Mechanical engineering and machinery|
|Deposited By:||En Mohd. Nazir Md. Basri|
|Deposited On:||01 Mar 2007 08:08|
|Last Modified:||19 May 2011 07:51|
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