References

• • J. Li, X. Yang, and P. F. Shi, “A fast level set approach to image segmentation based...
• • Y. Y. Gong, X. N. Luo, H. Huang, G. J. Liao, and Y. Zhang, “Multi-objects extracted b...
• • J. S. Xiao, H. Feng, and B. S. Yi, “Finite difference method for semilinear parabolic...
• • J. Lie, M. Lysaker, and X. C. Tai, “A binary level set model and some applications to...
• • G. E. P. Box and G. M. Jenkins, “Time series analysis, forecasting and control,” San ...
• • R. H. Myers, “Classical and modern regression with applications (2nd Edition),” Bosto...
• • S. A. Billings and S. Chen, “The determination of multivariable nonlinear models for ...
• • R. O. Duda and P. E. Hart, “Pattern classification and scene analysis,” New York: Wil...
• • C. M. Bishop, “Neural networks for pattern recognition,” Oxford, U.K.: Oxford Univers...
• • B. D. Ripley, “Pattern recognition and neural networks,” Cambridge, U. K.: Cambridge ...
• • E. Parzen, “On estimation of a probability density function and mode,” The Annals of ...
• • B. W. Silverman, “Density estimation for statistics and data analysis,” London: Chapm...
• • A. W. Bowman and A. Azzalini, “Applied smoothing techniques for data analysis,” Oxfor...
• • P. Eykhoff, “System identification: Parameter and state estimation,” Chichester, Engl...
• • G. C. Goodwin and R. L. Payne, “Dynamic system identification: Experiment design and ...
• • L. Ljung and T. S?derstr?m, “Theory and practice of recursive identification,” Cambri...
• • N. R. Draper and H. Smith, “Applied regression analysis,” New York: Wiley, 1981.
• • I. J. Leontaritis and S. A. Billings, “Input-output parametric models for non-linear ...
• • I. J. Leontaritis and S. A. Billings, “Model selection and validation methods for non...
• • S. Chen and S. A. Billings, “Representation of non- linear systems: The NARMAX model,...
• • J. Moody and C. J. Darken, “Fast learning in networks of locally-tuned processing uni...
• • Y. H. Pao, “Adaptive pattern recognition and neural networks,” Reading, MA: Addison-W...
• • S. Chen, S. A. Billings and P. M. Grant, “Non-linear system identification using neur...
• • K. S. Narendra and K. Parthasarathy, “Identification and control of dynamic systems u...
• • T. Poggio and F. Girosi, “Networks for approximation and learning,” Proceedings of IE...
• • T. D. Sanger, “A tree-structured adaptive network for function approximation in high-...
• • S. Chen and S. A. Billings, “Neural networks for non- linear dynamic system modelling...
• • D. J. C. MacKay, “Bayesian interpretation,” Neural Computation, Vol. 4, No. 3, pp. 41...
• • L. X. Wang, “Adaptive fuzzy systems and control: Design and stability analysis,” Pren...
• • J. Sjoberg, Q. Zhang, L. Ljung, A. Benveniste, B. Delyon, P. Glorennec, H. Hjalmarsso...
• • D. S. Broomhead and D. Lowe, “Multivariable function interpolation and adaptive netwo...
• • S. A. Billings and S. Chen, “Extended model set, global data and threshold model iden...
• • J. H. Friedman, “Multivariate adaptive regression splines,” The Annals of Statistics,...
• • L. X. Wang and J. M. Mendel, “Fuzzy basis functions, universal approximation, and ort...
• • T. Kavli, “ASMOD: An algorithm for adaptive spline modelling of observation data,” In...
• • M. Brown and C. J. Harris, “Neurofuzzy adaptive modelling and control,” Englewood Cli...
• • Q. H. Zhang, “Using wavelet network in nonparametric estimation,” IEEE Transactions o...
• • S. Chen, S. A. Billings, and W. Luo, “Orthogonal least squares methods and their appl...
• • S. Chen, C. F. N. Cowan, and P. M. Grant, “Orthogonal least squares learning algorith...
• • S. Chen and J. Wigger, “Fast orthogonal least squares algorithm for efficient subset ...