Identification Techniques for Mathematical Modeling of the Human Smooth Pursuit System

This thesis proposes nonlinear system identification techniques for the mathematical modeling of the human smooth pursuit system (SPS) with application to motor symptom quantification in Parkinson' ...

[1]  Peter Nauclér,et al.  Estimation and Control of Resonant Systems with Stochastic Disturbances , 2008 .

[2]  Metz Hs,et al.  Saccadic velocity measurements in strabismus. , 1983 .

[3]  George-Othon Glentis,et al.  Efficient algorithms for Volterra system identification , 1999, IEEE Trans. Signal Process..

[4]  Magnus Johansson Psi-calculi: a framework for mobile process calculi : Cook your own correct process calculus - just add data and logic , 2010 .

[5]  Petre Stoica,et al.  SPICE and LIKES: Two hyperparameter-free methods for sparse-parameter estimation , 2012, Signal Process..

[6]  Linda Brus,et al.  Nonlinear Identification and Control with Solar Energy Applications , 2008 .

[7]  V. Tikhomirov,et al.  {eta}-meson production in proton-proton collisions at excess energies of 40 and 72 MeV , 2010 .

[8]  Pawel Kasprowski,et al.  Eye Movements in Biometrics , 2004, ECCV Workshop BioAW.

[9]  Ruslan Fomkin Optimization and Execution of Complex Scientific Queries , 2009 .

[10]  Vasilis Z. Marmarelis,et al.  Comparative nonlinear modeling of renal autoregulation in rats: Volterra approach versus artificial neural networks , 1998, IEEE Trans. Neural Networks.

[11]  K. Rathsman Modeling of Electron Cooling : Theory, Data and Applications , 2010 .

[12]  W. Wu,et al.  Asymptotic theory for stationary processes , 2011 .

[13]  Aude Billard,et al.  Learning Stable Nonlinear Dynamical Systems With Gaussian Mixture Models , 2011, IEEE Transactions on Robotics.

[14]  Er-Wei Bai An optimal two-stage identification algorithm for Hammerstein-Wiener nonlinear systems , 1998, Autom..

[15]  Michel Verhaegen,et al.  Identifying MIMO Wiener systems using subspace model identification methods , 1996, Signal Process..

[16]  Bengt Carlsson Digital differential filters and model based fault detection , 1990 .

[17]  Alexander Medvedev,et al.  Mathematical modeling and grey-box identification of the human smooth pursuit mechanism , 2010, 2010 IEEE International Conference on Control Applications.

[18]  A. McSpadden A mathematical model of human saccadic eye movement , 1998 .

[19]  Hao He,et al.  Waveform Design for Active Sensing Systems: A Computational Approach , 2012 .

[20]  W. Greblicki Nonparametric identification of Wiener systems by orthogonal series , 1994, IEEE Trans. Autom. Control..

[21]  J. Rissanen,et al.  Modeling By Shortest Data Description* , 1978, Autom..

[22]  G. Avanzini,et al.  Oculomotor disorders in Huntington's chorea. , 1979, Journal of neurology, neurosurgery, and psychiatry.

[23]  Mats Ekman Modeling and Control of Bilinear Systems : Application to the Activated Sludge Process , 2005 .

[24]  Stephen T. Buckland,et al.  Fitting Density Functions with Polynomials , 1992 .

[25]  R. Gnanadesikan,et al.  Probability plotting methods for the analysis for the analysis of data , 1968 .

[26]  Peter S. Hammerstein Stochastic resonance and noise-assisted signal transfer : on coupling-effects of stochastic resonators and spectral optimization of fluctuations in random network switches , 2004 .

[27]  Stephen G Lisberger,et al.  Gain control in human smooth-pursuit eye movements. , 2002, Journal of neurophysiology.

[28]  Johan Petrini,et al.  Querying RDF Schema Views of Relational Databases , 2008 .

[29]  D. Robinson The mechanics of human saccadic eye movement , 1964, The Journal of physiology.

[30]  Per Åhgren On System Identification And Acoustic Echo Cancellation , 2004 .

[31]  R. Latham,et al.  The Cost Function , 1976 .

[32]  P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .

[33]  C. Rashbass,et al.  The relationship between saccadic and smooth tracking eye movements , 1961, The Journal of physiology.

[34]  W. Rugh Nonlinear System Theory: The Volterra / Wiener Approach , 1981 .

[35]  S. Marino,et al.  Quantitative Analysis of Pursuit Ocular Movements in Parkinson’s Disease by Using a Video-Based Eye Tracking System , 2007, European Neurology.

[36]  W. Newsome,et al.  Deficits in visual motion processing following ibotenic acid lesions of the middle temporal visual area of the macaque monkey , 1985, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[37]  Agnes Rensfelt,et al.  Viscoelastic Materials : Identification and Experiment Design , 2010 .

[38]  D. Robinson,et al.  The upper limit of human smooth pursuit velocity , 1985, Vision Research.

[39]  M. Maurin,et al.  REVIEW ARTICLE doi: 10.1111/j.1472-8206.2008.00633.x The Hill equation: a review of its capabilities in pharmacological modelling , 2008 .

[40]  Erik Larsson Identification of Stochastic Continuous-time Systems : Algorithms, Irregular Sampling and Cramér-Rao Bounds , 2003 .

[42]  C. Juhlin Seismic attenuation, shear wave anisotropy and some aspect of fracturing in the crystalline rock of the Siljan Ring area, central Sweden , 1990 .

[43]  Alexander Medvedev,et al.  Dynamic smooth pursuit gain estimation from eye tracking data , 2011, IEEE Conference on Decision and Control and European Control Conference.

[44]  Ulrich Büttner,et al.  A theory of the dual pathways for smooth pursuit based on dynamic gain control. , 2008, Journal of neurophysiology.

[45]  Johan Schoukens,et al.  Wiener system identification with generalized orthonormal basis functions , 2014, Autom..

[46]  Lennart Ljung,et al.  System Identification: Theory for the User , 1987 .

[47]  C Kennard,et al.  Ocular motor and manual tracking in Parkinson's disease and the effect of treatment. , 1987, Journal of neurology, neurosurgery, and psychiatry.

[48]  B. Wahlberg System identification using Laguerre models , 1991 .

[49]  J. L. Gordon,et al.  A model of the smooth pursuit eye movement system , 1986, Biological Cybernetics.

[50]  N. Wiener,et al.  Nonlinear Problems in Random Theory , 1964 .

[51]  Jonas Lindgren Waveform inversion of seismic reflection data through local optimisation methods , 1992 .

[52]  Anders Berglund,et al.  Learning computer systems in a distributed project course : The what, why, how and where , 2012 .

[53]  Feng Ding,et al.  Least squares based and gradient based iterative identification for Wiener nonlinear systems , 2011, Signal Process..

[54]  SchoukensJohan,et al.  Wiener system identification with generalized orthonormal basis functions , 2014 .

[55]  R. Gerchberg A practical algorithm for the determination of phase from image and diffraction plane pictures , 1972 .

[56]  Marcus Nilsson,et al.  Regular Model Checking , 2000, CAV.

[57]  Thomas Martinetz,et al.  A Single-Camera Remote Eye Tracker , 2006, PIT.

[58]  Hisao Suzuki,et al.  Activity of fixation neurons in the monkey frontal eye field during smooth pursuit eye movements. , 2014, Journal of neurophysiology.

[59]  J. Cogan,et al.  FIVE TYPES OF EYE MOVEMENT IN THE HORIZONTAL MERIDIAN PLANE OF THE FIELD OF REGARD , 2004 .

[60]  M. Schetzen The Volterra and Wiener Theories of Nonlinear Systems , 1980 .

[61]  Anne B. Sereno,et al.  Antisaccades and smooth pursuit eye movements in schizophrenia , 1995, Biological Psychiatry.

[62]  V. Marmarelis Identification of nonlinear biological systems using laguerre expansions of kernels , 1993, Annals of Biomedical Engineering.

[63]  Jan Henry Nyström,et al.  Analysing Fault Tolerance for Erlang Applications , 2009 .

[64]  R. Kronmal,et al.  On Multivariate Density Estimates Based on Orthogonal Expansions , 1970 .

[65]  Erik Gudmundson,et al.  Signal Processing for Spectroscopic Applications , 2010 .

[66]  Felix Wehrmann,et al.  On Modelling Nonlinear Variation in Discrete Appearances of Objects , 2004 .

[67]  Torbjörn Wigren Recursive identification based on the nonlinear Wiener model , 1990 .

[68]  Stephen A. Billings,et al.  Identi cation of nonlinear systems-A survey , 1980 .

[69]  Zygmunt Hasiewicz,et al.  On Nonparametric Identification of Wiener Systems , 2007, IEEE Transactions on Signal Processing.

[70]  H. Lilliefors On the Kolmogorov-Smirnov Test for Normality with Mean and Variance Unknown , 1967 .

[71]  Robin Strand Distance Functions & Image Processing on Point-lattices: With Focus on the 3d Face-&-body-centered Cubic Grids , 2008 .

[72]  Douglas A. Reynolds,et al.  Speaker Verification Using Adapted Gaussian Mixture Models , 2000, Digit. Signal Process..

[73]  Björn Halvarsson,et al.  Interaction Analysis in Multivariable Control Systems Applications to Bioreactors for Nitrogen Removal , 2010 .

[74]  Ignacio Santamaría,et al.  Blind Identification of SIMO Wiener Systems Based on Kernel Canonical Correlation Analysis , 2013, IEEE Transactions on Signal Processing.

[75]  Norbert Kathmann,et al.  Deficits in gain of smooth pursuit eye movements in schizophrenia and affective disorder patients and their unaffected relatives. , 2003, The American journal of psychiatry.

[76]  R. Dodge FIVE TYPES OF EYE MOVEMENT IN THE HORIZONTAL MERIDIAN PLANE OF THE FIELD OF REGARD , 1903 .

[77]  Robert W. Heath,et al.  Designing structured tight frames via an alternating projection method , 2005, IEEE Transactions on Information Theory.

[78]  Laurence R. Young,et al.  Variable Feedback Experiments Testing a Sampled Data Model for Eye Tracking Movements , 1963 .

[79]  Rik Pintelon,et al.  System Identification: A Frequency Domain Approach , 2012 .

[80]  A. Pohl Search for Subrelativistic Particles with the AMANDA Neutrino Telescope , 2009 .

[81]  John B. Shoven,et al.  I , Edinburgh Medical and Surgical Journal.

[82]  B. Wahlberg,et al.  Modelling and Identification with Rational Orthogonal Basis Functions , 2000 .

[83]  Gerald Cook,et al.  Derivation of a model for the human eye-positioning mechanism , 1967 .

[84]  Jesper Bengtson,et al.  Formalising process calculi , 2010 .

[85]  Jenny Persson,et al.  The Obvious & The Essential: Interpreting Software Development & Organizational Change , 2004 .