Abarbanel HD, Creveling DR, Jeanne JM. (2008). Estimation of parameters in nonlinear systems using balanced synchronization. Physical review. E, Statistical, nonlinear, and soft matter physics. 77 [PubMed]
Akesson BM, Jb_jrgensen , Poulsen NK, Sb_jrgensen . (2008). A generalized autocovariance leastsquares method for Kalman filter tu Journal Of Process Control. 18
Anderson JL, Anderson SL. (2011). Monte Carlo implementation of the nonlinear filtering problem to produce ensemble assimilations and forecasts American Meterological Society. 127
Behn CG, Brown EN, Scammell TE, Kopell NJ. (2007). Mathematical model of network dynamics governing mouse sleep-wake behavior. Journal of neurophysiology. 97 [PubMed]
Borbély AA. (1982). A two process model of sleep regulation. Human neurobiology. 1 [PubMed]
Chase RM, Pincus DB. (2011). Sleep-related problems in children and adolescents with anxiety disorders. Behavioral sleep medicine. 9 [PubMed]
Coogan AN, Thome J. (2011). Chronotherapeutics and psychiatry: setting the clock to relieve the symptoms. The world journal of biological psychiatry : the official journal of the World Federation of Societies of Biological Psychiatry. 12 Suppl 1 [PubMed]
Deng B, Wang J, Che Y. (2009). A combined method to estimate parameters of neuron from a heavily noise-corrupted time series of active potential. Chaos (Woodbury, N.Y.). 19 [PubMed]
Deurveilher S, Semba K. (2005). Indirect projections from the suprachiasmatic nucleus to major arousal-promoting cell groups in rat: implications for the circadian control of behavioural state. Neuroscience. 130 [PubMed]
Diniz Behn CG, Booth V. (2010). Simulating microinjection experiments in a novel model of the rat sleep-wake regulatory network. Journal of neurophysiology. 103 [PubMed]
Eberle C, Ament C. (2011). The Unscented Kalman Filter estimates the plasma insulin from glucose measurement. Bio Systems. 103 [PubMed]
Fleshner M, Booth V, Forger DB, Diniz Behn CG. (2011). Circadian regulation of sleep-wake behaviour in nocturnal rats requires multiple signals from suprachiasmatic nucleus. Philosophical transactions. Series A, Mathematical, physical, and engineering sciences. 369 [PubMed]
Freestone DR et al. (2011). A data-driven framework for neural field modeling. NeuroImage. 56 [PubMed]
Fuller PM, Saper CB, Lu J. (2007). The pontine REM switch: past and present. The Journal of physiology. 584 [PubMed]
Hattar S, Liao HW, Takao M, Berson DM, Yau KW. (2002). Melanopsin-containing retinal ganglion cells: architecture, projections, and intrinsic photosensitivity. Science (New York, N.Y.). 295 [PubMed]
Hofstra WA, de Weerd AW. (2009). The circadian rhythm and its interaction with human epilepsy: a review of literature. Sleep medicine reviews. 13 [PubMed]
Hu X et al. (2007). Estimation of hidden state variables of the Intracranial system using constrained nonlinear Kalman filters. IEEE transactions on bio-medical engineering. 54 [PubMed]
Huang D. (2004). Synchronization-based estimation of all parameters of chaotic systems from time series Phys Rev E. 69
Huang ZL, Urade Y, Hayaishi O. (2011). The role of adenosine in the regulation of sleep. Current topics in medicinal chemistry. 11 [PubMed]
Jacquez JA, Greif P. (1985). Numerical parameter identifiability and estimability: Integrating identifiability, estimability, and optimal sampling design Mathematical Biosciences. 77
Jatoth RK, Kumar TK. (2009). Particle swarm optimization based tuning of unscented Kalman filter for bearings only trackin Advances in Recent Technologies in Communication and Computing, 2009. ARTCom 09. International Conference.
Julier SJ, Uhlmann JK. (1997). A new extension of the Kalman filter to nonlinear systems P Spie. 3068
Kalman RE. (1960). A new approach to linear filtering and prediction problems Trans ASME J Basic Eng. 82
Kalman RE. (1960). On the general theory of control systems Proc Ifac 1st International Congress. 1
Kalnay E. (2003). mospheric modeling, data assimilation and predictability.
Konnur R. (2003). Synchronization-based approach for estimating all model parameters of chaotic systems. Physical review. E, Statistical, nonlinear, and soft matter physics. 67 [PubMed]
Korniyenko OV, Sharawi MS, Aloi DN. (2005). Neural network based approach for tuning KALMAN filter Electro Information Technology, 2005 IEEE International Conference.
Kothare SV, Zarowski M. (2011). Sleep and epilepsy: common bedfellows. Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society. 28 [PubMed]
Krout KE, Kawano J, Mettenleiter TC, Loewy AD. (2002). CNS inputs to the suprachiasmatic nucleus of the rat. Neuroscience. 110 [PubMed]
Letellier C, Aguirre L. (2010). Interplay between synchronization, observability, and dynamics. Phys Rev E 82: 1-11. PubMedID: And Dynamics Phys Rev E. 82
Letellier C, Aguirre LA. (2002). Investigating nonlinear dynamics from time series: The influence of symmetries and the choice of observables. Chaos (Woodbury, N.Y.). 12 [PubMed]
Letellier C, Aguirre LA. (2009). Symbolic observability coefficients for univariate and multivariate analysis. Physical review. E, Statistical, nonlinear, and soft matter physics. 79 [PubMed]
Letellier C, Aguirre LA, Maquet J. (2005). Relation between observability and differential embeddings for nonlinear dynamics. Physical review. E, Statistical, nonlinear, and soft matter physics. 71 [PubMed]
Lutz A, Odelson BJ, Rawlings JB. (2006). The autocovariance least-squares method for estimating covariances: application to model-based control of chemical reactors Ieee Transactions On Control Systems Technology. 14
Margaria G, Riccomagno E, White LJ. (2004). Structural identifiability analysis of some highly structured families of statespace models using differential algebra. Journal of mathematical biology. 49 [PubMed]
Margoliash D, Abarbanel H, Toth B, Kostuk M, Meliza C. (2006). Dynamical estimation of neuron and network properties I: variational methods Variational Methods Biological Cybernetics. 105
Maybhate A, Amritkar RE. (1999). Use of synchronization and adaptive control in parameter estimation from a time series Phys Rev E. 59
McCarley RW, Hobson JA. (1975). Neuronal excitability modulation over the sleep cycle: a structural and mathematical model. Science (New York, N.Y.). 189 [PubMed]
Mehra R. (1970). On the identification of variances and adaptiveKalman filtering Ieee Transactions On Automatic Control. 15
Michael AC, Borland LM. (2007). Eectrochemical Methods for Neuroscience, Chapter 19.
Miyoshi T. (2011). he Gaussian approach to adaptive covariance ination and its implementation with the local ensemble transform Monthly Weather Review. 139
Mohamed AH, Schwar Schwarz. (1999). Adaptive Kalman filtering for INS-GPS Journal Of Geodesy. 73
Ohno K, Sakurai T. (2008). Orexin neuronal circuitry: role in the regulation of sleep and wakefulness. Frontiers in neuroendocrinology. 29 [PubMed]
Parlitz U. (1996). Estimating model parameters from time series by autosynchronization. Physical review letters. 76 [PubMed]
Pecora LM, Carroll TL. (1990). Synchronization in chaotic systems. Physical review letters. 64 [PubMed]
Phillips AJ, Robinson PA. (2007). A quantitative model of sleep-wake dynamics based on the physiology of the brainstem ascending arousal system. Journal of biological rhythms. 22 [PubMed]
Porkka-Heiskanen T, Strecker RE, McCarley RW. (2000). Brain site-specificity of extracellular adenosine concentration changes during sleep deprivation and spontaneous sleep: an in vivo microdialysis study. Neuroscience. 99 [PubMed]
Quach M, Brunel N, d'Alché-Buc F. (2007). Estimating parameters and hidden variables in non-linear state-space models based on ODEs for biological networks inference. Bioinformatics (Oxford, England). 23 [PubMed]
Quigg M. (2000). Circadian rhythms: interactions with seizures and epilepsy. Epilepsy research. 42 [PubMed]
Raue A, Becker V, Klingmüller U, Timmer J. (2010). Identifiability and observability analysis for experimental design in nonlinear dynamical models. Chaos (Woodbury, N.Y.). 20 [PubMed]
Raue A et al. (2009). Structural and practical identifiability analysis of partially observed dynamical models by exploiting the profile likelihood. Bioinformatics (Oxford, England). 25 [PubMed]
Raue A, Kreutz C, Maiwald T, Klingmuller U, Timmer J. (2011). Addressing parameter identifiability by model-based experimentation. IET systems biology. 5 [PubMed]
Rawlings JB, Rajamani MR. (2009). Estimation of the disturbance structure from data using semidefinite programming and optimal weighting Automatica. 45
Rempe MJ, Best J, Terman D. (2010). A mathematical model of the sleep/wake cycle. Journal of mathematical biology. 60 [PubMed]
Saper CB, Scammell TE, Lu J. (2005). Hypothalamic regulation of sleep and circadian rhythms. Nature. 437 [PubMed]
Schiff SJ. (2010). Towards model-based control of Parkinson's disease. Philosophical transactions. Series A, Mathematical, physical, and engineering sciences. 368 [PubMed]
Schiff SJ. (2012). Neural Control Engineering.
Simon D. (2006). Optimal state estimation: Kalman, H [infinity] and nonlinear approaches.
Sunderam S et al. (2007). Improved sleep-wake and behavior discrimination using MEMS accelerometers. Journal of neuroscience methods. 163 [PubMed]
Tamakawa Y, Karashima A, Koyama Y, Katayama N, Nakao M. (2006). A quartet neural system model orchestrating sleep and wakefulness mechanisms. Journal of neurophysiology. 95 [PubMed]
Timmer J, Voss HU. (2004). onlinear dynamical system identification from uncertain and indirect measurements International Journal Of Bifurcation And Chaos. 14
Ullah G, Schiff SJ. (2010). Assimilating seizure dynamics. PLoS computational biology. 6 [PubMed]
Vaida F. (2005). Parameter convergence for EM and MM algorithms Statistica Sinica. 15
Van_domselaar B, Hemkar P. (1975). Nonlinear parameter estimation in initial value problems Technical report. Mathematical Centre Amsterdam.
Verwey M, Amir S. (2009). Food-entrainable circadian oscillators in the brain. The European journal of neuroscience. 30 [PubMed]
Wang J. (2000). Stochastic modeling for real-time kinematic GPS-GLONASS position Navigation. 46
Wu_jcf . (1983). On the convergence properties of the EM algorithm The Annals Of Statistics. 11