Most cited papers in Control Systems and Identification
What are the most cited papers in Control Systems and Identification?
The most cited paper in Control Systems and Identification is "Maximum Likelihood from Incomplete Data Via the EM Algorithm" (A. P. Dempster, N. M. Laird, Donald B. Rubin, 1977), with 50,034 citations. Next come "Learning representations by back-propagating errors" (32,003) and "Bootstrap Methods: Another Look at the Jackknife" (17,826).
Showing 50 of 99 papers. Every paper with more than 1,205 citations is listed.
| # | Paper | ||
|---|---|---|---|
| 1 | Maximum Likelihood from Incomplete Data Via the EM Algorithm A. P. Dempster, N. M. Laird, Donald B. Rubin · Journal of the Royal Statistical Society Series B (Statistical Methodology) | Sep 1977 | 50,034 |
| 2 | Learning representations by back-propagating errors David E. Rumelhart, Geoffrey E. Hinton, Ronald J. Williams · Nature | Oct 1986 | 32,003 |
| 3 | Bootstrap Methods: Another Look at the Jackknife B. Efron · The Annals of Statistics | 1979 | 17,826 |
| 4 | Fundamentals of Statistical Signal Processing: Estimation Theory Sailes K. Sengijpta · Technometrics | Nov 1995 | 11,254 |
| 5 | Least angle regression Bradley Efron, Trevor Hastie, Iain M. Johnstone et al. · The Annals of Statistics | Apr 2004 | 9,594 |
| 6 | Ridge Regression: Biased Estimation for Nonorthogonal Problems Arthur E. Hoerl, Robert W. Kennard · Technometrics | Feb 1970 | 9,491 |
| 7 | YALMIP : a toolbox for modeling and optimization in MATLAB Johan Löfberg | 21 Mar 2005 | 9,338 |
| 8 | Constrained model predictive control: Stability and optimality D.Q. Mayne, James B. Rawlings, Christopher V. Rao et al. · Automatica | Jun 2000 | 8,753 |
| 9 | Identification and control of dynamical systems using neural networks Kumpati S. Narendra, Kavya Parthasarathy · IEEE Transactions on Neural Networks | Mar 1990 | 8,035 |
| 10 | Model Selection and Estimation in Regression with Grouped Variables Ming Yuan, Yi Lin · Journal of the Royal Statistical Society Series B (Statistical Methodology) | 21 Dec 2005 | 7,568 |
| 11 | Decoding by Linear Programming Emmanuel J. Candès, Terence Tao · IEEE Transactions on Information Theory | 22 Nov 2005 | 7,371 |
| 12 | Partial least-squares regression: a tutorial Paul L. M. Geladi, Bruce R. Kowalski · Analytica Chimica Acta | 1986 | 7,034 |
| 13 | Regression and time series model selection in small samples Clifford M. Hurvich, Chih‐Ling Tsai · Biometrika | 1989 | 6,492 |
| 14 | Least-squares frequency analysis of unequally spaced data Nick Lomb · Astrophysics and Space Science | Feb 1976 | 5,834 |
| 15 | Gaussian Processes in Machine Learning Carl Edward Rasmussen · Lecture notes in computer science | 2004 | 5,379 |
| 16 | Model predictive control: Theory and practice—A survey Carlos E. García, David M. Prett, Manfred Morari · Automatica | May 1989 | 5,344 |
| 17 | Principal component analysis in linear systems: Controllability, observability, and model reduction B. C. Moore · IEEE Transactions on Automatic Control | Feb 1981 | 5,320 |
| 18 | A survey of industrial model predictive control technology S. Joe Qin, Thomas A. Badgwell · Control Engineering Practice | 30 Apr 2003 | 5,091 |
| 19 | Discovering governing equations from data by sparse identification of nonlinear dynamical systems Steven L. Brunton, Joshua L. Proctor, J. Nathan Kutz · Proceedings of the National Academy of Sciences | 28 Mar 2016 | 4,849 |
| 20 | A general regression neural network Donald F. Specht · IEEE Transactions on Neural Networks | 1991 | 4,518 |
| 21 | Essentials of robust control Kemin Zhou | 1998 | 3,839 |
| 22 | Regression Shrinkage and Selection via The Lasso: A Retrospective Robert John Tibshirani · Journal of the Royal Statistical Society Series B (Statistical Methodology) | 20 Apr 2011 | 3,710 |
| 23 | Detection of signals by information theoretic criteria M. Wax, T. Kailath · IEEE Transactions on Acoustics Speech and Signal Processing | Apr 1985 | 3,443 |
| 24 | Feedback Systems: Input-Output Properties C. Desoer, M. Vidyasagar, Alan N. Willson · Journal of Dynamic Systems Measurement and Control | Dec 1975 | 3,251 |
| 25 | A linear matrix inequality approach to H ∞ control Pascal M. Gahinet, Pierre Apkarian · International Journal of Robust and Nonlinear Control | 1994 | 3,238 |
| 26 | The estimation of the gradient of a density function, with applications in pattern recognition Keinosuke Fukunaga, Larry D. Hostetler · IEEE Transactions on Information Theory | 1975 | 3,082 |
| 27 | All optimal Hankel-norm approximations of linear multivariable systems and their L , ∞ -error bounds† K. Glover · International Journal of Control | Jun 1984 | 2,882 |
| 28 | Optimization of Control Parameters for Genetic Algorithms John J. Grefenstette · IEEE Transactions on Systems Man and Cybernetics | 1986 | 2,869 |
| 29 | Sure Independence Screening for Ultrahigh Dimensional Feature Space Jianqing Fan, Jinchi Lv · Journal of the Royal Statistical Society Series B (Statistical Methodology) | 3 Oct 2008 | 2,851 |
| 30 | Support Vector Method for Function Approximation, Regression Estimation, and Signal Processing Vladimir N. Vapnik, Steven E. Golowich, Alex J. Smola | 1996 | 2,702 |
| 31 | An introduction to observers David G. Luenberger · IEEE Transactions on Automatic Control | Dec 1971 | 2,688 |
| 32 | Ridge Regression: Applications to Nonorthogonal Problems Arthur E. Hoerl, Robert W. Kennard · Technometrics | Feb 1970 | 2,666 |
| 33 | Approximating discrete probability distributions with dependence trees Chee Lap Chow, C. Liu · IEEE Transactions on Information Theory | May 1968 | 2,654 |
| 34 | Feedback and optimal sensitivity: Model reference transformations, multiplicative seminorms, and approximate inverses G. Zames · IEEE Transactions on Automatic Control | Apr 1981 | 2,372 |
| 35 | Process fault detection based on modeling and estimation methods—A survey Rolf Isermann · Automatica | Jul 1984 | 2,354 |
| 36 | Model predictive control: past, present and future Manfred Morari, Jay H. Lee · Computers & Chemical Engineering | May 1999 | 2,342 |
| 37 | Subspace identification for linear systems: theory, implementation, applications Peter Van Overschee, Bart L. R. De Moor · CERN Document Server (European Organization for Nuclear Research) | 1996 | 2,280 |
| 38 | Multivariable feedback design: Concepts for a classical/modern synthesis John C. Doyle, G. Stein · IEEE Transactions on Automatic Control | Feb 1981 | 2,205 |
| 39 | Gaussian networks for direct adaptive control R.M. Sanner, J.-J.E. Slotine · IEEE Transactions on Neural Networks | 1992 | 2,204 |
| 40 | H/sub ∞/ design with pole placement constraints: an LMI approach M. Chilali, Pascal M. Gahinet · IEEE Transactions on Automatic Control | Mar 1996 | 2,174 |
| 41 | A survey of design methods for failure detection in dynamic systems Alan S. Willsky · Automatica | Nov 1976 | 2,144 |
| 42 | Opposition-Based Learning: A New Scheme for Machine Intelligence Hamid R. Tizhoosh | 25 May 2006 | 2,140 |
| 43 | Projection Pursuit Regression Jerome H. Friedman, Werner Stuetzle · Journal of the American Statistical Association | Dec 1981 | 2,117 |
| 44 | N4SID: Subspace algorithms for the identification of combined deterministic-stochastic systems Peter Van Overschee, Bart De Moor · Automatica | 1994 | 1,985 |
| 45 | Model predictive control: Recent developments and future promise D.Q. Mayne · Automatica | 11 Nov 2014 | 1,979 |
| 46 | Nonlinear black-box modeling in system identification: a unified overview Jonas Sigfrid Sjoberg, Qinghua Zhang, Lennart Ljung et al. · Automatica | Dec 1995 | 1,937 |
| 47 | The Divergence and Bhattacharyya Distance Measures in Signal Selection T. Kailath · IRE Transactions on Communications Systems | Feb 1967 | 1,884 |
| 48 | Neural networks for control systems—A survey Kate Hunt, Daniel G. Sbarbaro, R. Żbikowski et al. · Automatica | Nov 1992 | 1,871 |
| 49 | The outranking approach and the foundations of electre methods Bernard Roy · Theory and Decision | Jul 1991 | 1,855 |
| 50 | Tutorial on maximum likelihood estimation In Jae Myung · Journal of Mathematical Psychology | Feb 2003 | 1,830 |
Citations are OpenAlex's own counts, from its 2026-09-23 snapshot, so the ranking can differ from Google Scholar or Web of Science. A paper is listed for a field when OpenAlex files it under one of the field's topics; retracted papers and papers whose citation count cannot be traced to citing works are left out, and a preprint and the article it became are shown once. Release dates are OpenAlex's: where a source gave only a month or a year, that is what is shown. How the lists are chosen.