Structural Reformulations in System Identification
暂无分享,去创建一个
[1] Robert E. Mahony,et al. Optimization Algorithms on Matrix Manifolds , 2007 .
[2] Ker-Chau Li,et al. On almost Linearity of Low Dimensional Projections from High Dimensional Data , 1993 .
[3] K. Edström. Switched Bond Graphs : Simulation and Analysis , 1999 .
[4] M. Verhaegen,et al. Identifying MIMO Wiener systems using subspace model identification methods , 1995, Proceedings of 1995 34th IEEE Conference on Decision and Control.
[5] Fredrik Gunnarsson,et al. Uplink load in CDMA cellular radio systems , 2006, IEEE Transactions on Vehicular Technology.
[6] Henrik Ohlsson,et al. Regularization for Sparseness and Smoothness : Applications in System Identification and Signal Processing , 2010 .
[7] P. Pucar,et al. On the Hinge-Finding Algorithm for Hinging Hyperplanes , 1998, IEEE Trans. Inf. Theory.
[8] Michael A. Saunders,et al. LSQR: An Algorithm for Sparse Linear Equations and Sparse Least Squares , 1982, TOMS.
[9] R. Tibshirani. Regression Shrinkage and Selection via the Lasso , 1996 .
[10] M. Fliess,et al. Nonlinear observability, identifiability, and persistent trajectories , 1991, [1991] Proceedings of the 30th IEEE Conference on Decision and Control.
[11] B. Wahlberg,et al. Modelling and Identification with Rational Orthogonal Basis Functions , 2000 .
[12] Christina Grönwall. Ground Object Recognition using Laser Radar Data : Geometric Fitting, Performance Analysis, and Applications , 2006 .
[13] Lexin Li,et al. Sufficient dimension reduction via bayesian mixture modeling. , 2011, Biometrics.
[14] B. Li,et al. Dimension reduction for nonelliptically distributed predictors , 2009, 0904.3842.
[15] Jianqing Fan,et al. Local polynomial modelling and its applications , 1994 .
[16] Mikael Norrlöf,et al. Iterative Learning Control : Analysis, Design, and Experiments , 2000 .
[17] Tommy Svensson. Mathematical Tools and Software for Analysis and Design of Nonlinear Control Systems , 1992 .
[18] Stephen P. Boyd,et al. A rank minimization heuristic with application to minimum order system approximation , 2001, Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148).
[19] W. Rudin. Principles of mathematical analysis , 1964 .
[20] Daniel Axehill,et al. Integer Quadratic Programming for Control and Communication , 2008 .
[21] J. Sjöberg. Optimal Control and Model Reduction of Nonlinear DAE Models , 2008 .
[22] Han-Ming Wu. Kernel Sliced Inverse Regression with Applications to Classification , 2008 .
[23] R. Cook,et al. Estimating the structural dimension of regressions via parametric inverse regression , 2001 .
[24] Ali H. Sayed,et al. Linear Estimation (Information and System Sciences Series) , 2000 .
[25] R. Durrett. Probability: Theory and Examples , 1993 .
[26] R. Cook,et al. Sufficient Dimension Reduction via Inverse Regression , 2005 .
[27] Sun-Yuan Kung,et al. A new identification and model reduction algorithm via singular value decomposition , 1978 .
[28] Per-Johan Nordlund,et al. Efficient Estimation and Detection Methods for Airborne Applications , 2008 .
[29] Jeroen D. Hol,et al. Sensor Fusion and Calibration of Inertial Sensors, Vision, Ultra-Wideband and GPS , 2011 .
[30] Adam Krzyzak,et al. A Distribution-Free Theory of Nonparametric Regression , 2002, Springer series in statistics.
[31] Dietmar Bauer,et al. Estimating ARMAX systems for multivariate time series using the state approach to subspace algorithms , 2009, J. Multivar. Anal..
[32] B. Moor,et al. Subspace identification for linear systems , 1996 .
[33] Jonas Elbornsson,et al. Analysis, Estimation and Compensation of Mismatch Effects in A/D Converters , 2003 .
[34] Frida Eng,et al. Non-Uniform Sampling in Statistical Signal Processing , 2007 .
[35] Anders Helmersson,et al. Methods for robust gain scheduling , 1995 .
[36] S. Glad. Solvability of differential algebraic equations and inequalities: An algorithm , 1997, 1997 European Control Conference (ECC).
[37] R. Cook,et al. Reweighting to Achieve Elliptically Contoured Covariates in Regression , 1994 .
[38] Petre Stoica,et al. Estimating Optimal Weights for Instrumental Variable Methods , 2001, Digit. Signal Process..
[39] Gene H. Golub,et al. Matrix computations , 1983 .
[40] John W. Tukey,et al. A Projection Pursuit Algorithm for Exploratory Data Analysis , 1974, IEEE Transactions on Computers.
[41] S. Weisberg,et al. Comments on "Sliced inverse regression for dimension reduction" by K. C. Li , 1991 .
[42] S. Diop. A state elimination procedure for nonlinear systems , 1989 .
[43] Yingcun Xia,et al. Sliced Regression for Dimension Reduction , 2008 .
[44] H. Tong,et al. An adaptive estimation of dimension reduction , 2002 .
[45] T. Söderström. On the uniqueness of maximum likelihood identification , 1975, Autom..
[46] Leon O. Chua,et al. Fading memory and the problem of approximating nonlinear operators with volterra series , 1985 .
[47] Yu Zhu,et al. Fourier Methods for Estimating the Central Subspace and the Central Mean Subspace in Regression , 2006 .
[48] Michel Verhaegen,et al. Filtering and System Identification: Frontmatter , 2007 .
[49] M. L. Eaton. A characterization of spherical distributions , 1986 .
[50] Jiao Yang,et al. Dimension estimation in sufficient dimension reduction: A unifying approach , 2011, J. Multivar. Anal..
[51] Petre Stoica,et al. Decentralized Control , 2018, The Control Systems Handbook.
[52] J. Friedman. Exploratory Projection Pursuit , 1987 .
[53] Daniel Ankelhed,et al. On design of low order H-infinity controllers , 2011 .
[54] Michael I. Jordan,et al. Kernel dimension reduction in regression , 2009, 0908.1854.
[55] S. Andersson. On Dimension Reduction in Sensor Array Signal Processing , 1992 .
[56] Predrag Pucar. Modeling and Segmentation using Multiple Models , 1995 .
[57] Ragnar Wallin,et al. Optimization Algorithms for System Analysis and Identification , 2004 .
[58] Niclas Bergman,et al. Recursive Bayesian Estimation : Navigation and Tracking Applications , 1999 .
[59] S. Kotsios. An application of Ritt’s remainder algorithm to discrete polynomial control systems , 2001 .
[60] Abbas Emami-Naeini,et al. Feedback Control of Dynamic Systems (6th edition) , 2010 .
[61] R. Weiss,et al. Using the Bootstrap to Select One of a New Class of Dimension Reduction Methods , 2003 .
[62] Lexin Li,et al. Cluster-based estimation for sufficient dimension reduction , 2004, Comput. Stat. Data Anal..
[63] Petre Stoica,et al. MIMO system identification: state-space and subspace approximations versus transfer function and instrumental variables , 2000, IEEE Trans. Signal Process..
[64] Yurii Nesterov,et al. Introductory Lectures on Convex Optimization - A Basic Course , 2014, Applied Optimization.
[65] Lennart Ljung,et al. Difference algebra and system identification , 2011, at - Automatisierungstechnik.
[66] S. Kotsios,et al. The model matching problem for a certain class of nonlinear systems , 1993 .
[67] P. Misra,et al. Numerically reliable computation of characteristic polynomials , 1995, Proceedings of 1995 American Control Conference - ACC'95.
[68] Jonathan R. Partington,et al. On linear models for nonlinear systems , 2003, Autom..
[69] J. Durbin. EFFICIENT ESTIMATION OF PARAMETERS IN MOVING-AVERAGE MODELS , 1959 .
[70] J. Ramos,et al. A Null-Space-Based Technique for the Estimation of Linear-Time Invariant Structured State-Space Representations , 2012 .
[71] H. Fortell. Algebraic Approaches to Normal Forms and Zero Dynamics , 1995 .
[72] J. Saracco,et al. Cluster-based Sliced Inverse Regression , 2010 .
[73] Yves Rolain,et al. Parametric MIMO parallel Wiener identification , 2011, IEEE Conference on Decision and Control and European Control Conference.
[74] Sette Diop,et al. Elimination in control theory , 1991, Math. Control. Signals Syst..
[75] G. Hendeby,et al. Performance and Implementation Aspects of Nonlinear Filtering , 2008 .
[76] K. Forsman. Constructive Commutative Algebra in Nonlinear Control Theory , 1991 .
[77] Rickard Karlsson,et al. Particle filtering for positioning and tracking applications , 2005 .
[78] Andreas Eidehall,et al. Tracking and threat assessment for automotive collision avoidance , 2007 .
[79] Lennart Ljung,et al. NONLINEAR DYNAMICS IDENTIFIED BY MULTI-INDEX MODELS , 2005 .
[80] T. Söderström,et al. Instrumental variable methods for system identification , 1983 .
[81] E. Kolchin. Differential Algebra and Algebraic Groups , 2012 .
[82] Bart Vandereycken,et al. Low-Rank Matrix Completion by Riemannian Optimization , 2013, SIAM J. Optim..
[83] A. Seidenberg. An elimination theory for differential algebra , 1959 .
[84] J. Löfberg. Minimax approaches to robust model predictive control , 2003 .
[85] Robin Sibson,et al. What is projection pursuit , 1987 .
[86] Ingela Lind,et al. Regressor and Structure Selection Uses of ANOVA in System Identification , 2006 .
[87] Emmanuel J. Candès,et al. Exact Matrix Completion via Convex Optimization , 2009, Found. Comput. Math..
[88] Michel Verhaegen,et al. Filtering and System Identification: Kalman filtering , 2007 .
[89] Svante Gunnarsson. Frequency Domain Aspects of Modeling and Control in Adaptive Systems , 1988 .
[90] Peng Zeng,et al. An integral transform method for estimating the central mean and central subspaces , 2010, J. Multivar. Anal..
[91] Urban Forssell. Closed-loop Identification : Methods, Theory, and Applications , 1999 .
[92] Stephen P. Boyd,et al. Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.
[93] D. L. Hanson,et al. On the strong law of large numbers for a class of stochastic processes , 1963 .
[94] Ker-Chau Li,et al. Sliced Inverse Regression for Dimension Reduction , 1991 .
[95] Parikshit Shah,et al. Linear system identification via atomic norm regularization , 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).
[96] B. Wahlberg. On the Identification and Approximation of Linear Systems , 1987 .
[97] J. Borwein,et al. Convex Analysis And Nonlinear Optimization , 2000 .
[98] Lennart Ljung,et al. Estimate Physical Parameters by Black Box Modeling , 2003 .
[99] Fredrik Tjärnström,et al. Variance Expressions and Model Reduction in System Identification , 2002 .
[100] Dietmar Bauer,et al. ESTIMATING LINEAR DYNAMICAL SYSTEMS USING SUBSPACE METHODS , 2005, Econometric Theory.
[101] Lieven Vandenberghe,et al. Interior-Point Method for Nuclear Norm Approximation with Application to System Identification , 2009, SIAM J. Matrix Anal. Appl..
[102] Christian Lundquist,et al. Extended Target Tracking using a Gaussian-Mixture PHD Filter , 2017, IEEE Transactions on Aerospace and Electronic Systems.
[103] J. Ritt. Partial differential algebra , 1950 .
[104] Christian Lundquist,et al. Sensor fusion for automotive applications , 2011 .
[105] Kjell Nordström. Uncertainty, Robustness and Sensitivity Reduction in the Design of Single Input Control Systems , 1987 .
[106] Martin Enqvist,et al. A weighting method for approximate nonlinear system identification , 2007, 2007 46th IEEE Conference on Decision and Control.
[107] Alberto Bemporad,et al. Identification of piecewise affine systems via mixed-integer programming , 2004, Autom..
[108] K. Fang,et al. Asymptotics for kernel estimate of sliced inverse regression , 1996 .
[109] P. Lindskog. Methods, Algorithms and Tools for System Identification Based on Prior Knowledge , 1996 .
[110] Lennart Ljung,et al. On global identifiability for arbitrary model parametrizations , 1994, Autom..
[111] Johan A. K. Suykens,et al. Nuclear norm regularization for overparametrized Hammerstein systems , 2010, 49th IEEE Conference on Decision and Control (CDC).
[112] Mats Viberg,et al. Subspace fitting concepts in sensor array processing , 1990 .
[113] Jan-Erik Strömberg,et al. A Mode Switching Modelling Philosophy , 1994 .
[114] B. Wahlberg. System identification using Laguerre models , 1991 .
[115] Julian J. Bussgang,et al. Crosscorrelation functions of amplitude-distorted gaussian signals , 1952 .
[116] Jakob Roll. Local and Piecewise Affine Approaches to System Identification , 2003 .
[117] Magnus Larsson,et al. Behavioral and Structural Model Based Approaches to Discrete Diagnosis , 1999 .
[118] Berkant Savas,et al. Rank reduction and volume minimization approach to state-space subspace system identification , 2006, Signal Process..
[119] Vladimir Pavlovic,et al. Central Subspace Dimensionality Reduction Using Covariance Operators , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[120] Per Skoglar,et al. Tracking and Planning for Surveillance Applications , 2012 .
[121] B. Wahlberg. System identification using Kautz models , 1994, IEEE Trans. Autom. Control..
[122] Lennart Ljung,et al. Estimating Linear Time-invariant Models of Nonlinear Time-varying Systems , 2001, Eur. J. Control.
[123] A. Gut. Probability: A Graduate Course , 2005 .
[124] M. Fliess,et al. Flatness and defect of non-linear systems: introductory theory and examples , 1995 .
[125] B. Bengtsson. On some Control Problems for Queues , 1982 .
[126] Xiangrong Yin,et al. Sliced Inverse Regression with Regularizations , 2008, Biometrics.
[127] S. Yun,et al. An accelerated proximal gradient algorithm for nuclear norm regularized linear least squares problems , 2009 .
[128] Yingxing Li,et al. On hybrid methods of inverse regression-based algorithms , 2007, Comput. Stat. Data Anal..
[129] Valur Einarsson. Model Checking Methods for Mode Switching Systems , 2000 .
[130] Henrik Tidefelt,et al. Differential-algebraic equations and matrix-valued singular perturbation , 2009 .
[131] Lixing Zhu,et al. Dimension Reduction in Regressions Through Cumulative Slicing Estimation , 2010 .
[132] Allan Gut,et al. An intermediate course in probability , 1995 .
[133] Albert H. Nuttall. Theory and application of the separable class of random processes , 1958 .
[134] J. Friedman,et al. Projection Pursuit Regression , 1981 .
[135] Bruno Buchberger,et al. A theoretical basis for the reduction of polynomials to canonical forms , 1976, SIGS.
[136] Lennart Ljung,et al. Handling Certain Structure Information in Subspace Identification , 2009 .
[137] Jieping Ye,et al. An accelerated gradient method for trace norm minimization , 2009, ICML '09.
[138] Lixing Zhu,et al. Asymptotics for sliced average variance estimation , 2007, 0708.0462.
[139] Maarten Schoukens,et al. Combining the Best Linear Approximation and Dimension Reduction to Identify the Linear Blocks of Parallel Wiener Systems , 2013, ALCOSP.
[140] Lixing Zhu,et al. Asymptotics of sliced inverse regression , 1995 .
[141] L.R.J. Haverkamp,et al. State space identification - Theory and practice , 2001 .
[142] Stig Moberg,et al. Modeling and Control of Flexible Manipulators , 2007 .
[143] Yue-Ping Jiang,et al. Recursive identification of MIMO Wiener systems with general inputs , 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.
[144] E. Bai. An optimal two stage identification algorithm for Hammerstein-Wiener nonlinear systems , 1998 .
[145] Gene F. Franklin,et al. Feedback Control of Dynamic Systems , 1986 .
[146] H. Luetkepohl. The Handbook of Matrices , 1996 .
[147] Johanna Wallén,et al. Estimation-based iterative learning control , 2011 .
[148] H. Akçay,et al. An efficient frequency domain state-space identification algorithm , 1994, Proceedings of 1994 33rd IEEE Conference on Decision and Control.
[149] David Törnqvist,et al. Estimation and Detection with Applications to Navigation , 2008 .
[150] Thomas M. Stoker,et al. Investigating Smooth Multiple Regression by the Method of Average Derivatives , 2015 .
[151] W. Härdle,et al. Optimal Smoothing in Single-index Models , 1993 .
[152] Paul Tseng,et al. Hankel Matrix Rank Minimization with Applications to System Identification and Realization , 2013, SIAM J. Matrix Anal. Appl..
[153] Shaoli Wang,et al. On Directional Regression for Dimension Reduction , 2007 .
[154] Martin S. Andersen,et al. A convex relaxation of a dimension reduction problem using the nuclear norm , 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).
[155] Torsten Söderström,et al. Discrete-time Stochastic Systems , 2002 .
[156] Jonas Gillberg. Frequency Domain Identification of Continuous-Time Systems : Reconstruction and Robustness , 2006 .
[157] Lennart Ljung,et al. Identification Aspects of Ritt's Algorithm for Discrete-Time Systems , 2009 .
[158] Lennart Ljung,et al. System identification toolbox for use with MATLAB , 1988 .
[159] Liping Zhu,et al. A Semiparametric Approach to Dimension Reduction , 2012, Journal of the American Statistical Association.
[160] R. Irving,et al. Integers, Polynomials, and Rings: A Course in Algebra , 2003 .
[161] Petre Stoica,et al. Spectral Analysis of Signals , 2009 .
[162] G. Strang. Introduction to Linear Algebra , 1993 .
[163] R. Dennis Cook,et al. Estimating central subspaces via inverse third moments , 2003 .
[164] Håkan Hjalmarsson. Aspects on Incomplete Modeling in System Identification , 1993 .
[165] Inderjit S. Dhillon,et al. Guaranteed Rank Minimization via Singular Value Projection , 2009, NIPS.
[166] Bing Li,et al. Dimension reduction for non-elliptically distributed predictors: second-order methods , 2010 .
[167] Mille Millnert. Identification and Control of Systems Subject to Abrupt Changes , 1983 .
[168] Yitzhak Katznelson,et al. A (terse) introduction to linear algebra , 2007 .
[169] J. Sjöberg. Non-Linear System Identification with Neural Networks , 1995 .
[170] Hugues Garnier,et al. Numerical illustrations of the relevance of direct continuous-time model identification , 2002 .
[171] Christian Lyzell,et al. Sliced Inverse Regression for the Identification of Dynamical Systems , 2012 .
[172] Bo Wahlberg,et al. Analysis of state space system identification methods based on instrumental variables and subspace fitting , 1997, Autom..
[173] Y. Xia. A constructive approach to the estimation of dimension reduction directions , 2007, math/0701761.
[174] Lixing Zhu,et al. Sufficient dimension reduction through discretization-expectation estimation , 2010 .
[175] Xavier Bombois,et al. Necessary and sufficient conditions for uniqueness of the minimum in Prediction Error Identification , 2012, Autom..
[176] Liuping Wang,et al. Identification of Continuous-time Models from Sampled Data , 2008 .
[177] Lennart Ljung,et al. System Identification: Theory for the User , 1987 .
[178] T. Glad,et al. An Algebraic Approach to Linear and Nonlinear Control , 1993 .
[179] Bart De Moor,et al. Continuous-time frequency domain subspace system identification , 1996, Signal Process..
[180] Alan Edelman,et al. The Geometry of Algorithms with Orthogonality Constraints , 1998, SIAM J. Matrix Anal. Appl..
[181] Efstathia Bura. Using linear smoothers to assess the structural dimension of regressions , 2001 .
[182] Peter A. J. Nagy. Tools for Knowledge-Based Signal Processing with Applications to System Identification , 1992 .
[183] A. Tsybakov,et al. Bandwidth Choice for Average Derivative Estimation , 1992 .
[184] Anders Stenman,et al. Model on Demand: Algorithms, Analysis and Applications , 1999 .
[185] Guido De Roeck,et al. Subspace identification of (AR)ARMAX, Box-Jenkins, and generalized model structures , 2009 .
[186] Carl D. Meyer,et al. Matrix Analysis and Applied Linear Algebra , 2000 .
[187] Christian Lyzell,et al. Inverse Regression for the Wiener Class of Systems , 2012 .
[188] David Williams,et al. Probability with Martingales , 1991, Cambridge mathematical textbooks.
[189] J. Gunnarsson. Symbolic Methods and Tools for Discrete Event Dynamic Systems , 1997 .
[190] M. Fliess. Automatique en temps discret et algèbre aux différences , 1990 .
[191] Tao Wang,et al. Sparse sufficient dimension reduction using optimal scoring , 2013, Comput. Stat. Data Anal..
[192] Inger Klein,et al. Automatic Synthesis of Sequential Control Schemes , 1993 .
[193] Lennart Ljung,et al. Adaptive control based on explicit criterion minimization , 1985, Autom..
[194] Lixing Zhu,et al. On Sliced Inverse Regression With High-Dimensional Covariates , 2006 .
[195] E. Bai,et al. Block Oriented Nonlinear System Identification , 2010 .
[196] Bo Wahlberg,et al. A linear regression approach to state-space subspace system identification , 1996, Signal Process..
[197] T. McKelvey. Identification of State-Space Models from Time and Frequency Data , 1995 .
[198] Stephen J. Wright,et al. Numerical Optimization , 2018, Fundamental Statistical Inference.
[199] H. Zha,et al. Contour regression: A general approach to dimension reduction , 2005, math/0508277.
[200] M. Jirstrand. Constructive Methods for Inequality Constraints in Control , 1998 .
[201] Ker-Chau Li,et al. On Principal Hessian Directions for Data Visualization and Dimension Reduction: Another Application of Stein's Lemma , 1992 .
[202] Ke Wang-Chen. Transformation and Symbolic Calculations in Filtering and Control , 1994 .
[203] Robert Tibshirani,et al. The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition , 2001, Springer Series in Statistics.
[204] M. Schetzen. The Volterra and Wiener Theories of Nonlinear Systems , 1980 .
[205] R. Dennis Cook,et al. A note on shrinkage sliced inverse regression , 2005 .
[206] H. Jonson. A Newton Method for Solving Non-Linear Optimal Control Problems with General Constraints , 1983 .
[207] S. Glad. Implementing Ritt’s Algorithm of Differential Algebra , 1992 .
[208] A. Isaksson. On System Identification in one and two Dimensions with Signal Processing Applications , 1988 .
[209] F. Gustafsson. Estimation of Discrete Parameters in Linear Systems , 1993 .
[210] Fredrik Gunnarsson. Power control in cellular radio system: Analysis, design and estimation , 2000 .
[211] Heinz Kredel,et al. Gröbner Bases: A Computational Approach to Commutative Algebra , 1993 .
[212] Liping Zhu,et al. On kernel method for sliced average variance estimation , 2007 .