Hassen Mekki, Mohamed Chtourou, "Variable Structure Neural Networks for Real Time Approximation of Continuous Time Dynamical Systems Using Evolutionary Artificial Potential Fields," WSEAS Transactions on Systems, vol. 11, pp. -, 2012, DOI:
Hassen Mekki, Mohamed Chtourou. Variable Structure Neural Networks for Real Time Approximation of Continuous Time Dynamical Systems Using Evolutionary Artificial Potential Fields.
WSEAS Transactions on Systems. 2012;11:-.
WSEAS Transactions on Systems
Print ISSN: 1109-2777, E-ISSN: 2224-2678
Volume 11, 2012
Variable Structure Neural Networks for Real Time Approximation of Continuous Time Dynamical Systems Using Evolutionary Artificial Potential Fields
Authors: ,
Abstract: A novel neural network architecture, is proposed and shown to be useful in approximating the unknown nonlinearities of dynamical systems. In the variable structure neural network, the number of basis functions can be either increased or decreased this is
Keywords:
Variable structure neural network, Radial basis functions, Evolutionary artificial fields, Identification of dynamical systems
Pages: - WSEAS Transactions on Systems, ISSN / E-ISSN: 1109-2777 / 2224-2678, Volume 11, 2012DOI: *As the DOI is a unique identifier, it is already available in the pdf version.
**The DOI link will be activated in the first midst of January 2026.
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