1. [1] L. Ljung: System Identification: Theory for The User, 2nd ed., Prentice-Hall PTR, 1999.
2. [2] M.A. Jami'in, I. Sutrisno, and J. Hu: Deep searching for parameter estimation of the linear time invariant (LTI) system by using quasi-ARX neural network, Proceedings of The 2013 International Joint Conference on Neural Networks (IJCNN2013), pp. 2758-2762, 2013.
3. [3] H. Yu, T.T. Xie, S. Paszczynski, and B.M. Wilamowski: Advantages of radial basis function networks for dynamic system design, IEEE Trans. Ind. Electron, Vol. 58, No. 12, pp. 5438-5440, 2012.
4. [4] M.Z. Hou and X.L. Han: Constructive approximation to multivariate function by decay RBF neural network, IEEE Trans. Neural Netw., Vol. 21, No. 9, pp. 1517-1523, 2009.
5. [5] K. Dalamagkidis, K.P. Valavanis, and L.A. Piegl: Nonlinear model predictive control with neural network optimization for autonomous autorotation of small unmanned helicopters, IEEE Trans. Control Syst. Technol., Vol. 19, No. 4, pp. 818-831, 2011.