Chaotic system identification using Wiener‐LSSVM model

[1]  R. Konnur.  Synchronization-based approach for estimating all model parameters of chaotic systems. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[2]  Zongben Xu,et al.  Universal Approximation of Extreme Learning Machine With Adaptive Growth of Hidden Nodes , 2012, IEEE Transactions on Neural Networks and Learning Systems.

[3]  Johan A. K. Suykens,et al.  Least-Squares Support Vector Machines for the Identification of Wiener-Hammerstein Systems , 2012 .

[4]  Vladimir N. Vapnik,et al.  The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[5]  Christopher J. C. Burges,et al.  A Tutorial on Support Vector Machines for Pattern Recognition , 1998, Data Mining and Knowledge Discovery.

[6]  Guanrong Chen,et al.  Identifying chaotic systems using Wiener and Hammerstein cascade models , 2001 .

[7]  L X Wang,et al.  Fuzzy basis functions, universal approximation, and orthogonal least-squares learning , 1992, IEEE Trans. Neural Networks.

[8]  Leandro dos Santos Coelho,et al.  Identification of the Hénon chaotic map by fuzzy modeling and Nelder–Mead simplex method , 2009 .

[9]  Changjin Wang,et al.  Predict the Time Series of the Parameter-Varying Chaotic System Based on Reduced Recursive Lease Square Support Vector Machine , 2009, 2009 International Conference on Artificial Intelligence and Computational Intelligence.

[10]  Peng Shi,et al.  Sampled-Data Fuzzy Control of Chaotic Systems Based on a T–S Fuzzy Model , 2014, IEEE Transactions on Fuzzy Systems.

[11]  Li-Qun Chen,et al.  Projective lag synchronization of spatiotemporal chaos via active sliding mode control , 2012 .

[12]  Min Han,et al.  Support Vector Echo-State Machine for Chaotic Time-Series Prediction , 2007, IEEE Transactions on Neural Networks.

[13]  Hisao Ishibuchi,et al.  Multiobjective genetic fuzzy rule selection with fuzzy relational rules , 2013, 2013 IEEE International Workshop on Genetic and Evolutionary Fuzzy Systems (GEFS).

[14]  Jilei Zhou,et al.  Connections among several chaos feedback control approaches and chaotic vibration control of mechanical systems , 2014, Commun. Nonlinear Sci. Numer. Simul..

[15]  Chih-Min Lin,et al.  An Efficient Interval Type-2 Fuzzy CMAC for Chaos Time-Series Prediction and Synchronization , 2014, IEEE Transactions on Cybernetics.

[16]  Peng Shi,et al.  Sampled-Data Synchronization of Chaotic Lur'e Systems With Time Delays , 2013, IEEE Transactions on Neural Networks and Learning Systems.

[17]  Qi Wu,et al.  The forecasting model based on wavelet nu-support vector machine , 2009, Expert Syst. Appl..

[18]  Somayeh Raiesdana,et al.  Study on chaos anti-control for hippocampal models of epilepsy , 2013, Neurocomputing.

[19]  Eduardo Liz,et al.  Prediction-based control of chaos and a dynamic Parrondoʼs paradox , 2013 .

[20]  Guanrong Chen,et al.  From Chaos to Order - Perspectives and Methodologies in Controlling Chaotic Nonlinear Dynamical Systems , 1993 .

[21]  Mehdi Sadeghpour,et al.  Intelligent control of chaos using linear feedback controller and neural network identifier , 2012 .

[22]  Javier Moreno-Valenzuela.  Adaptive anti control of chaos for robot manipulators with experimental evaluations , 2013, Commun. Nonlinear Sci. Numer. Simul..

[23]  Jose C. Principe,et al.  Prediction of Chaotic Time Series with Neural Networks , 1992 .

[24]  Han Xiao,et al.  Parameters identification of chaotic system by chaotic gravitational search algorithm , 2012, Chaos, Solitons & Fractals.

[25]  Johan A. K. Suykens,et al.  Least Squares Support Vector Machine Classifiers , 1999, Neural Processing Letters.

[26]  Hak-Keung Lam,et al.  Tuning of the structure and parameters of a neural network using an improved genetic algorithm , 2003, IEEE Trans. Neural Networks.

[27]  Ying Chen,et al.  Identifying chaotic systems via a Wiener-type cascade model , 1997 .

[28]  J. Yeh.  Identifying chaotic systems using a fuzzy model coupled with a linear plant , 2007 .

[29]  Kumpati S. Narendra,et al.  Identification and control of dynamical systems using neural networks , 1990, IEEE Trans. Neural Networks.

[30]  Tzuu-Hseng S. Li,et al.  Hybrid Taguchi-chaos of multilevel immune and the artificial bee colony algorithm for parameter identification of chaotic systems , 2012, Comput. Math. Appl..

[31]  Chia-Feng Juang,et al.  TS-fuzzy system-based support vector regression , 2009, Fuzzy Sets Syst..

[32]  Chuandong Li,et al.  Chaos control and synchronization via a novel chatter free sliding mode control strategy , 2011, Neurocomputing.

[33]  Parlitz,et al.  Estimating model parameters from time series by autosynchronization. , 1996, Physical review letters.

[34]  Mohammad Hassan Khooban,et al.  Control of a class of non-linear uncertain chaotic systems via an optimal Type-2 fuzzy proportional integral derivative controller , 2013 .