Qualitative Validation of Radial Basis Function Networks

In system identification applications of neural networks, the aim is usually to obtain a dynamically valid model of the system which can be used for system analysis and for controller design. In the present study, a cell to cell mapping procedure is adopted for the global analysis of nonlinear systems and the qualitative validation of radial basis function networks. The method is used to graphically display the dynamic properties of nonlinear systems in a cell state space, including the fixed points, periodic and aperiodic solutions or chaotic behaviour and the corresponding stability properties. The orthogonal least squares algorithm (OLS) is then used to train a radial basis function network and the trained network is analysed using the cell mapping framework.....