Prediction of chaotic time series using L-GEM based RBFNN

• Published in: 2009 International Conference on Machine Learning and Cybernetics Vol. 2; pp. 1172 - 1177
• Main Authors: Hai-Lan Ding, Yeung, D.S., Qian-Li Ma, Ng, W.W.Y., Dong-Liang Wu, Jin-Cheng Li
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.07.2009
• Subjects: Autoregressive processes; Chaos; Chaotic communication; Chaotic time series prediction; Cybernetics; Localized Generalization Error Model; Machine learning; Neural networks; Neurons; Nonlinear dynamical systems; Prediction methods; Predictive models; RBFNN

The prediction of chaotic time series is a vital problem in nonlinear dynamical system. Radial Basis Function Neural Network (RBFNN) has been widely adopted in nonlinear dynamical system identification because of its simple topological structure, fast learning and strong extrapolating capability. Th...