A combined observer and filter based approach for the determination of unknown parameters
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[1] Denis Dochain,et al. State and parameter estimation in chemical and biochemical processes: a tutorial , 2003 .
[2] Philip Denbigh,et al. System analysis and signal processing: with emphasis on the use of MATLAB , 1998 .
[3] Bruno A. Olshausen,et al. Book Review , 2003, Journal of Cognitive Neuroscience.
[4] G. Ermentrout,et al. Analysis of neural excitability and oscillations , 1989 .
[5] Jaime A. Moreno,et al. PASSIVITY AND UNKNOWN INPUT OBSERVERS FOR NONLINEAR SYSTEMS , 2002 .
[6] Alberto Isidori,et al. Nonlinear control systems: an introduction (2nd ed.) , 1989 .
[7] R. Marino. Adaptive observers for single output nonlinear systems , 1990 .
[8] Robert Haber. Nonlinear System Identification : Input-output Modeling Approach , 1999 .
[9] C. Morris,et al. Voltage oscillations in the barnacle giant muscle fiber. , 1981, Biophysical journal.
[10] Bruce Smaill,et al. Hodgkin-Huxley type ion channel characterization: an improved method of voltage clamp experiment parameter estimation. , 2006, Journal of theoretical biology.
[11] P. Gage,et al. Conventional Voltage Clamping With Two Intracellular Microelectrodes , 1985 .
[12] Miroslav Krstic,et al. Nonlinear and adaptive control de-sign , 1995 .
[13] Andreas Kugi,et al. Symbolic Computation For The Analysis AndSynthesis Of Nonlinear Control Systems , 1999 .
[14] Arthur J. Krener,et al. Linearization by output injection and nonlinear observers , 1983 .
[15] H. Nijmeijer,et al. New directions in nonlinear observer design , 1999 .
[16] A. Isidori. Nonlinear Control Systems: An Introduction , 1986 .
[17] Riccardo Marino,et al. Nonlinear control design: geometric, adaptive and robust , 1995 .
[18] Shahab Sheikholeslam. Observer-Based Parameter Identifiers for Nonlinear Systems with Parameter Dependencies , 1993, 1993 American Control Conference.
[19] Stanley H. Johnson,et al. Use of Hammerstein Models in Identification of Nonlinear Systems , 1991 .
[20] R. Marino,et al. Adaptive observers with arbitrary exponential rate of convergence for nonlinear systems , 1995, IEEE Trans. Autom. Control..
[21] S. Van Huffel,et al. SLICOT system identification software and applications , 2002, Proceedings. IEEE International Symposium on Computer Aided Control System Design.
[22] Ute Feldmann,et al. Communication by chaotic signals: the inverse system approach , 1995, Proceedings of ISCAS'95 - International Symposium on Circuits and Systems.
[23] H. Sebastian Seung,et al. The Autapse: A Simple Illustration of Short-Term Analog Memory Storage by Tuned Synaptic Feedback , 2004, Journal of Computational Neuroscience.
[24] S. Sastry,et al. Adaptive Control: Stability, Convergence and Robustness , 1989 .
[25] Bram de Jager. Symbolic calculation of zero dynamics for nonlinear control systems , 1991, ISSAC '91.
[26] G. Besançon. Remarks on nonlinear adaptive observer design , 2000 .
[27] H. G. Kwatny,et al. Nonlinear Control and Analytical Mechanics: A Computational Approach , 2001 .
[28] Ute Feldmann,et al. On the design of a synchronizing inverse of a chaotic system , 1995 .
[29] John Guckenheimer,et al. An Improved Parameter Estimation Method for Hodgkin-Huxley Models , 1999, Journal of Computational Neuroscience.
[30] M. Gevers,et al. Stable adaptive observers for nonlinear time-varying systems , 1987 .
[31] G. L. Amicucci,et al. On nonlinear detectability , 1998 .
[32] Jaime A. Moreno,et al. Unknown input observers for SISO nonlinear systems , 2000, Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187).
[33] J. Gauthier,et al. A simple observer for nonlinear systems applications to bioreactors , 1992 .
[34] D. Johnston,et al. Foundations of Cellular Neurophysiology , 1994 .
[35] Albert J. Rosa,et al. The Analysis and Design of Linear Circuits , 1993 .
[36] Harry G. Kwatny,et al. Nonlinear Control and Analytical Mechanics: A Computational Approach , 2000 .
[37] P. S. Sastry,et al. Memory neuron networks for identification and control of dynamical systems , 1994, IEEE Trans. Neural Networks.
[38] Paris A. Mastorocostas,et al. A recurrent fuzzy-neural model for dynamic system identification , 2002, IEEE Trans. Syst. Man Cybern. Part B.
[39] G. Kreisselmeier. Adaptive observers with exponential rate of convergence , 1977 .
[40] Richard Bertram,et al. A calcium-based phantom bursting model for pancreatic islets , 2004, Bulletin of mathematical biology.
[41] Andreas Griewank,et al. Evaluating derivatives - principles and techniques of algorithmic differentiation, Second Edition , 2000, Frontiers in applied mathematics.
[42] Lennart Ljung,et al. System Identification: Theory for the User , 1987 .
[43] H. Lecar,et al. Voltage and Patch Clamping with Microelectrodes , 1985, Springer New York.
[45] Rolf Isermann,et al. Identifikation dynamischer Systeme , 1988 .
[46] H. Fortell,et al. Calculation of zero dynamics using the Ritt algorithm , 1994, Proceedings of 1994 33rd IEEE Conference on Decision and Control.
[47] B. Sakmann,et al. Single-channel currents recorded from membrane of denervated frog muscle fibres , 1976, Nature.
[48] Philip Denbigh,et al. System analysis and signal processing , 1998 .
[49] C. Koch,et al. Methods in Neuronal Modeling: From Ions to Networks , 1998 .
[50] M. J. Korenberg,et al. The identification of nonlinear biological systems: Wiener and Hammerstein cascade models , 1986, Biological Cybernetics.