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Publications - Lieven Vandenberghe

See Google Scholar for a more complete list.

Books

Papers

  • X. Jiang, L. Vandenberghe, Bregman three-operator splitting methods, Journal of Optimization Theory and Applications, 2022. [link to published article]

  • X. Jiang, L. Vandenberghe, Bregman primal–dual first-order method and application to sparse semidefinite programming. Computational Optimization and Applications, 2022. [link to published article]

  • H.-H. Chao, L. Vandenberghe, Entropic proximal operators for nonnegative trigonometric polynomials. IEEE Transactions on Signal Processing, 2018. [preprint pdf] Related software: [directory]

  • Y. Yue, L. Vandenberghe, W.K. Wong, T-optimal designs for multi-factor polynomial regression models via semidefinite relaxation method. Statistics and Computing, 2018. [arXiv:1807:08213 preprint]

  • H.-H. Chao, L. Vandenberghe, Semidefinite representations of gauge functions for structured low-rank matrix decomposition. SIAM J. Optimization 27, 1362-1389, 2017. [pdf] [arXiv:1604:02500 preprint]

  • J. Li, M. S. Andersen, L. Vandenberghe, Inexact proximal Newton methods for self-concordant functions. Mathematical Methods of Operations Research 85, 19-41 , 2016. [pdf] [link to final version]

  • H.-H. Chao, L. Vandenberghe, Extensions of semidefinite programming methods for atomic decomposition. Proc. ICASSP, 4757-4761, 2016. [pdf]

  • Y. Sun, L. Vandenberghe, Decomposition methods for sparse matrix nearness problems. SIAM J. Matrix Analysis and Applications 36, 1691-1717, 2015 [pdf]. Related software: [directory], [zip file].

  • L. Vandenberghe, M. S. Andersen, Chordal graphs and semidefinite optimization. Foundations and Trends in Optimization 1, 241-433, 2014 [pdf] [link to final version].

  • D. O’Connor, L. Vandenberghe, Primal-dual decomposition by operator splitting and applications to image deblurring, SIAM J. Imaging Sciences 7, 1724-1754, 2014 [pdf]. Related software: [directory], [zip file].

  • M. S. Andersen, A. Hansson, L. Vandenberghe, Reduced-complexity semidefinite relaxations of optimal power flow problems, IEEE Transactions on Power Systems 29, 1855-1863, 2014 [arXiv:1308.6718 preprint].

  • A. Hansson, L. Vandenberghe, Sampling method for semidefinite programs with nonnegative Popov function constraints, International Journal of Control 87, 330-345, 2013 [pdf].

  • Z. Liu, A. Hansson, L. Vandenberghe, Nuclear norm system identification with missing inputs and outputs, System and Control Letters 62, 605-612, 2013 [pdf].

  • M. S. Andersen, J. Dahl, L. Vandenberghe, Logarithmic barriers for sparse matrix cones, Optimization Methods and Software 28, 396-423, 2013 [arXiv:1203:2742 preprint].

  • R. Halvgaard, J. B. Jørgensen, N. K. Poulsen, H. Madsen, L. Vandenberghe, Decentralized large-scale power balancing, Proceedings of the 4th European Innovative Smart Grid Technologies Conference (ISGT), 2013.

  • A. Hansson, Z. Liu, L. Vandenberghe, Subspace system identification via weighted nuclear norm optimization, Proc. CDC, 3439-3444, 2012 [arXiv:1207.0023 preprint].

  • L. Vandenberghe, Convex optimization techniques in system identification, Proc. IFAC Symposium on System Identfication, 71-76, 2012 [pdf].

  • G. Pipeleers, L. Vandenberghe, Generalized KYP lemma with real data, IEEE Transactions on Automatic Control, 56, 2942-2946, 2011 [pdf].

  • M. S. Andersen, J. Dahl, Z. Liu, L. Vandenberghe, Interior-point methods for large-scale cone programming. In: S. Sra, S. Nowozin, S. J. Wright (Editors) Optimization for Machine Learning, MIT Press (2011), 55-83 [pdf].

  • L. Vandenberghe, The CVXOPT linear and quadratic cone program solvers [pdf].

  • J. Songsiri, L. Vandenberghe, Topology selection in graphical models of autoregressive processes, Journal of Machine Learning Research, 11, 2671-2705, 2010 [pdf].

  • M. S. Andersen, L. Vandenberghe, J. Dahl, Linear matrix inequalities with chordal sparsity patterns and applications to robust quadratic optimization, in Proc. IEEE CACSD, 2010 [pdf].

  • M. S. Andersen, L. Vandenberghe, Support vector machine training using matrix completion techniques. Unpublished report [pdf] [Related software].

  • M. S. Andersen, J. Dahl, L. Vandenberghe, Implementation of nonsymmetric interior-point methods for linear optimization over sparse matrix cones, Mathematical Programming Computation, 2010 [Journal link] [software].

  • J. Kim, L. Vandenberghe, C.-K. Yang, Convex piecewise-linear modeling method for circuit optimization via geometric programming, IEEE Transactions on Computer-Aided Design, 1823-1827 (29), 2010.

  • D. Axehill, L. Vandenberghe, A. Hansson. Convex relaxations for mixed integer predictive control, Automatica 46, 1540-1545, 2010.

  • J. Songsiri, J. Dahl, L. Vandenberghe, Graphical models of autoregressive processes. In: Y. Eldar and D. Palomar, editors, Convex Optimization in Signal Processing and Communications, Cambridge University Press (2010), 89-116 [pdf].

  • Z. Liu and L. Vandenberghe, Semidefinite programming methods for system realization and identification. Proc. CDC, 4676-4681, 2009 [pdf].

  • Z. Liu, L. Vandenberghe, Interior-point method for nuclear norm approximation with application to system identification, SIAM Journal on Matrix Analysis and Applications, 31(3), 1235-1256, 2009 [pdf] [software].

  • B. H. Cheng, L. Vandenberghe, K. Yao, Distributed algorithm for node localization in wireless ad-hoc networks, ACM Transactions on Sensor Networks 6, 20 pages, 2009.

  • B. Demeulenaere, G. Pipeleers, J. De Caigny, J. Swevers, J. De Schutter, L. Vandenberghe, Optimal splines for rigid motion systems: a convex programming framework, Journal of Mechanical Design 131, 11 pages, 2009.

  • G. Pipeleers, B. Demeulenaere, J. Swevers, L. Vandenberghe, Extended LMI characterizations for stability and performance of linear systems, Systems & Control Letters 58, 510-518, 2009.

  • J. Songsiri, J. Dahl, L. Vandenberghe, Maximum-likelihood estimation of autoregressive models with conditional independence constraints, Proc. ICASSP, 1701-1704, 2009 [pdf].

  • J. Dahl, L. Vandenberghe, V. Roychowdhury, Covariance selection for non-chordal graphs via chordal embedding, Optimization Methods and Software 23 (4), 501-520, 2008 [pdf].

  • J. Cong, J. Lee, L. Vandenberghe, Robust gate sizing via mean excess delay minimization, Proc. ISPD, 10-14, 2008 [pdf].

  • Y. Lu, V. Roychowdhury, L. Vandenberghe. Distributed parallel support vector machines in strongly connected networks, IEEE Trans. Neural Networks 19, 1167-1178, 2008.

  • M. Nouralishahi, C. Wu, L. Vandenberghe, Model calibration for optical lithography via semidefinite programming, Optimization and Engineering 9, 19-35, 2008 [pdf].

  • Z. Liu, L. Vandenberghe, Low-rank structure in semidefinite programs derived from the KYP lemma, Proc. CDC, 5652-5659, 2007 [pdf].

  • D. Axehill, A. Hansson, L. Vandenberghe, Relaxations applicable to mixed integer predictive control  —  Comparisons and efficient computations, Proc. CDC, 4103-4109, 2007.

  • T. Roh, B. Dumitrescu, L. Vandenberghe, Multidimensional FIR filter design via trigonometric sum-of-squares optimization, IEEE Journal of Selected Topics in Signal Processing 1, 641-650, 2007 [pdf].

  • S. Boyd, S. Kim, L. Vandenberghe, A. Hassibi, A tutorial on geometric programming, Optimization and Engineering 8, 67-127, 2007 [pdf].

  • L. Vandenberghe, S. Boyd, K. Comanor, Generalized Chebyshev bounds via semidefinite programming, SIAM Review 49, 52-64, 2007 [pdf].

  • J. Lee, G. Hatcher, L. Vandenberghe, C.-K. K. Yang, Evaluation of fully-integrated switching regulators for CMOS process technologies, IEEE Trans. VLSI Systems 15 , 1017-1027, 2007.

  • D. Axehill, L. Vandenberghe, A. Hansson, On relaxations applicable to model predictive control for systems with binary control signals, Preprints of the 7th IFAC Symposium on Nonlinear Control Systems (NOLCOS), 200-205, 2007.

  • R. S. Prabhu, B. Daneshrad, L. Vandenberghe, Energy minimization of a QAM system, Proc. IEEE Wireless Communications and Networking Conference (WCNC), 729-734, 2007.

  • T. Roh, B. Dumitrescu, L. Vandenberghe, Interior-point algorithms for sum-of-squares optimization of multidimensional trigonometric polynomials, Proc. ICASSP, (III) 905-908, 2007 [pdf].

  • T. Roh, L. Vandenberghe, Discrete transforms, semidefinite programming, and sum-of-squares representations of nonnegative polynomials, SIAM J. Opt. 16, 939-964, 2006 [pdf].

  • P. Van Mieghem, L. Vandenberghe, Trade-off curves for QOS routing, IEEE INFOCOM 2006 [pdf].

  • K. Comanor, L. Vandenberghe, S. Boyd, Semidefinite programming and multivariate Chebyshev bounds, Proc. IFAC Symposium on Robust Control Design, 2006 [pdf].

  • J. Dahl, V. Roychowdhury, L. Vandenberghe, Maximum likelihood estimation of Gaussian graphical models: Numerical implementation and topology selection. Technical report (originally submitted to Journal of Machine Learning Research), 2005 [pdf].

  • L. Vandenberghe, V. Balakrishnan, R. Wallin, A. Hansson, T. Roh, Interior-point methods for semidefinite programming problems derived from the KYP lemma In: D. Henrion and A. Garulli, editors, Positive Polynomials in Control, Springer Verlag (2005), 195-238 [pdf].

  • B.H. Cheng, L. Vandenberghe, K. Yao, Semidefinite programming bounds on the probability of errors of binary communication systems with inexactly known intersymbol interference, IEEE Trans. Inf. Theory 51, 2951-2954, 2005.

  • B.H. Cheng, R.E. Hudson, F. Lorenzelli, L. Vandenberghe, K. Yao, Distributed Gauss-Newton method for node localization in wireless sensor networks, Proc. IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2005.

  • J. Kim. J. Lee., L. Vandenberghe, C-K. Yang, Techniques for improving the accuracy of geometric programming based analog circuit design optimization, Proc. ICCAD, 863-870, 2004.

  • L. Vandenberghe, V. Balakrishnan, R. Wallin, A. Hansson, On the implementation of primal-dual interior-point methods for semidefinite programming problems derived from the KYP lemma, Proc. CDC, 4658-4663, 2003 [pdf].

  • V. Balakrishnan, L. Vandenberghe, Semidefinite programming duality and linear time-invariant systems, IEEE Trans. Aut. Control 48, 30-41, 2003 [pdf]. A longer version is available as a technical report.

  • K. Comanor, L. Vandenberghe, A sequential analytic centering approach to the support vector machine, Proc. SPIE Advanced Signal Processing Algorithms, Architectures, and Implementations] (5205), 209-218, 2003 [pdf].

  • L. Vandenberghe, V. Balakrishnan, R. Wallin, A. Hansson, On the implementation of primal-dual interior-point methods for semidefinite programming problems derived from the KYP lemma, Proc. CDC, 4658-4663, 2003,

  • L. Yip, K. Comanor, J. C. Chen, R. E. Hudson, K. Yao, L. Vandenberghe, Array processing for target DOA, localization, and classification based on AML and SVM algorithms in sensor networks. In: F. Zhao and L. Guibas (Editors), Information Processing in Sensor Networks, Proceedings of the Second International Workshop on Sensor Networks (IPSN), 269-284, 2003

  • J. Dahl, L. Vandenberghe, B. H. Fleury, Approximate maximum-likelihood estimation using semidefinite programming, Proc. ICASSP, Volume VI, 721-724, 2003.

  • B. Alkire, L. Vandenberghe, Convex optimization problems involving finite autocorrelation sequences, Mathematical Programming, Series A 93, 331-359, 2002 [pdf].

  • L. Vandenberghe, S. Boyd, M. Nouralishahi, Robust linear programming and optimal control, Proc. IFAC World Congress on Automatic Control, 2002 [pdf]. A longer version (originally submitted to Automatica) is available as a 2001 technical report.

  • J. Dahl, L. Vandenberghe, B. H. Fleury, Robust least-squares estimators based on semidefinite programming, Proc. Asilomar Conf. Signals, Systems and Computers, 1787-1790, 2002.

  • S. Boyd, L. Vandenberghe, A. El Gamal, S. Yun, Design of robust global power and ground networks, Proc. ISPD, 2001 [pdf].

  • B. Alkire, L. Vandenberghe, Interior-point methods for magnitude filter design, Proc. ICASSP, 3821-3824, 2001 [pdf].

  • L. Vandenberghe, S. Boyd, S.-P. Wu, Semidefinite programming and determinant maximization. In: C.A. Floudas and P.M. Pardalos (Editors), Encyclopedia of Optimization, Volume 5, 128-132, Kluwer Academic Publishers, 2001.

  • C. Komninakis, L. Vandenberghe, R.D. Wesel, Capacity of the binomial channel, or minimax redundancy for memoryless sources, Proc. IEEE International Symposium on Information Theory, 127, 2001.

  • A. Hansson, L. Vandenberghe, A primal-dual potential reduction method for integral quadratic constraints, Proc. ACC, 3013-3017, 2001.

  • B. Alkire, L. Vandenberghe, Handling nonnegative constraints in spectral estimation, Proc. IEEE Asilomar Conf. Signals, Systems and Computers, 202-206, 2000 [pdf].

  • A. Hansson, L. Vandenberghe, Efficient solution of linear matrix inequalities for integral quadratic constraints, Proc. CDC, 5033-5034, 2000.

  • V. Balakrishnan, F. Wang, L. Vandenberghe, Applications of semidefinite programming in process control, Proc. ACC, 3219-3223, 2000.

  • L. Vandenberghe, V. Balakrishnan, Semidefinite programming duality and linear system theory: connections and implications for computation, Proc. CDC, 989-994, 1999 [pdf].

  • L. Vandenberghe, S. Boyd, Applications of semidefinite programming, Applied Numerical Mathematics 29, 283-299, 1999 [pdf].

  • L. Vandenberghe, V. Balakrishnan, Semidefinite programming duality and linear system theory: Connections and implications for computation, Proc. CDC, 989-994, 1999.

  • M. Lobo, L. Vandenberghe, S. Boyd, H. Lebret, Applications of second-order cone programming, Linear Algebra and its Applications 284, 193-228, 1998 [pdf].

  • L. Vandenberghe, S. Boyd, A. El Gamal, Optimizing dominant time constant in RC circuits, IEEE Trans. on Computer Aided Design 17, 110-125, 1998. [pdf].

  • L. Vandenberghe, S. Boyd, S. Wu, Determinant maximization with linear matrix inequality constraints, SIAM J. Matrix Analysis and Applications 19, 499-533, 1998 [pdf].

  • L. Vandenberghe, S. Boyd, Connections between semi-infinite and semidefinite programming. In: R. Reemtsen and J. J. Rueckmann, editors, Semi-infinite Programming, 277-294, Kluwer Academic Publishers, 1998 [pdf].

  • S.-P. Wu, S. Boyd, L. Vandenberghe, FIR filter design via spectral factorization and convex optimization, In: Biswa Datta, ed., Applied and Computational Control, Signals and Circuits, 215-245, Birkhauser, 1998 [pdf].

  • S.P. Wu, S. Boyd, L. Vandenberghe, FIR filter design via spectral factorization and convex optimization, Proceedings of the 32nd Annual Conference on Information Sciences and Systems (CISS), 418-419, 1998.

  • V. Balakrishnan, L. Vandenberghe, Linear matrix inequalities for signal processing. An overview, Proceedings of the 32nd Annual Conference on Information Sciences and Systems (CISS), 412-417, 1998.

  • L. Vandenberghe, S. Boyd, A. El Gamal, Optimal wire and transistor sizing for circuits with non-tree topology, Proc. ICCAD, 252-259, 1997 [pdf].

  • L. Vandenberghe, V. Balakrishnan, Algorithms and software for LMI problems in control, IEEE Control Systems Magazine, 89-95, 1997 [pdf].

  • S. Boyd, L. Vandenberghe, Semidefinite programming relaxations of non-convex problems in control and combinatorial optimization. In: A. Paulraj, V. Roychowdhury, and C. Schaper, editors, Communications, Computation, Control and Signal Processing: a Tribute to Thomas Kailath, 279-287, Kluwer, 1997 [pdf].

  • E. Beran, L. Vandenberghe, S. Boyd, A global BMI algorithm based on the generalized Benders decomposition, Proceedings European Control Conference, 1997 [pdf].

  • L. Vandenberghe, S. Boyd, Semidefinite programming, SIAM Review 38, 49-95, 1996 [pdf].

  • V. Balakrishnan, L. Vandenberghe, An application of semidefinite programming duality to derive bounds on the H_infty norm of a transfer matrix, Proc. CDC 3629-3630, 1996.

  • S.P. Wu, S. Boyd, L. Vandenberghe, FIR filter design via semidefinite programming and spectral factorization, Proc. CDC, 271-276, 1996 [pdf].

  • G. B. Javorzky, I. Kollar, L. Vandenberghe, S. Boyd, S.-P. Wu, Optimal excitation signal design for frequency domain system identification using semidefinite programming, Proceedings of the 8th IMEKO TC4 Symposium on Recent Advances in Electrical Measurements, 1996 [pdf].

  • L. Vandenberghe, V. Balakrishnan, Algorithms and software tools for LMI problems in control: an overview, Proc. of the IEEE International Conference on Computer-Aided Control System Design, 229-234, 1996.

  • L. Vandenberghe, S. Boyd, A primal-dual potential reduction method for problems involving matrix inequalities, Mathematical Programming, Series B, 205-236, 1995 [pdf].

  • V. Balakrishnan, L. Vandenberghe, Connections between duality in control theory and convex optimization, Proc. ACC, 4030-4034, 1995 [pdf].

  • J. Vandewalle, L. Vandenberghe, Piecewise-linear analysis. In: W.K. Chen (Editor), The Circuits and Filters Handbook 1034-1057, CRC Press, 1995.

  • S. Boyd, L. Vandenberghe, M. Grant, Efficient convex optimization for engineering design, Proc. IFAC Symposium on Robust Control Design, 14-23, 1994 [pdf].

  • L. Vandenberghe, S. Boyd, Positive definite programming. In: J. R. Birge and K. G. Murty (Editors), Mathematical Programming. State of the Art 1994, 276-308, The University of Michigan, 1994.

  • L. Vandenberghe, S. Boyd, Polynomial-time algorithm for determining quadratic Lyapunov functions for nonlinear systems, Proc. of the European Conference on Circuit Theory and Design, 1065-1068, 1993 [pdf].

  • L. Vandenberghe, J. Vandewalle, A path-following method for finding multiple equilibrium points in cellular neural networks, International Journal of Circuit Theory and Applications 20, 519-531, 1992.

  • B. De Moor, L. Vandenberghe, J. Vandewalle, The generalized linear complementarity problem and an algorithm to find all its solutions, Mathematical Programming, 57, 415-426, 1992.

  • L. Vandenberghe, J. Vandewalle, Variable dimension algorithms in the analysis of nonlinear circuits and systems, Proceedings of the International Seminar on Nonlinear Circuits and Systems 1 (Moscow, June 1992), 180-189, 1992.

  • L. Vandenberghe, J. Vandewalle, A variable dimension algorithm for solving harmonic balance equations, Proc. ISCAS, 1992.

  • L. Vandenberghe, J. Vandewalle, A continuous deformation algorithm for DC-analysis of active nonlinear circuits, Journal of Circuits, Systems and Computers 1, 327-351, 1991.

  • L. Vandenberghe, J. Vandewalle, DC-Analysis of active circuits by continuous deformation, Proceedings of the European Conference on Circuit Theory and Design 855-863, 1991.

  • L. Vandenberghe, J. Vandewalle, The computation of equilibrium points in cellular neural networks using complementary pivoting, Proceedings of the European Conference on Circuit Theory and Design, 30-38, 1991.

  • L. Vandenberghe, J. Vandewalle, A continuous deformation method for resistive circuits containing active and non-reciprocal elements, Proc. ISCAS, 762-765, 1991.

  • L. Vandenberghe, J. Vandewalle, Variable dimension algorithms in circuit theory, Proceedings of the IEEE Benelux/ProRISC Symposium on Circuits, Systems and Signal Processing, 101-104, 1991.

  • L. Vandenberghe, J. Vandewalle, Variable dimension algorithms for solving resistive circuits, International Journal of Circuit Theory and Applications 18, 443-474, 1990.

  • L. Vandenberghe, J. Vandewalle, Finding multiple equilibrium points of cellular neural networks without enumeration, Proceedings of the 1990 IEEE International Workshop on Cellular Neural Networks and their Applications, 45-54, 1990.

  • L. Vandenberghe, J. Vandewalle, Application of relaxation methods to the adaptive training of neural networks. In: M.A. Kaashoek, J.H. van Schuppen and A.C.M. Ran (Editors), Signal Processing, Scattering and Operator Theory, and Numerical Methods, Proceedings MTNS-89 3, 189-196, Birkhauser, 1990.

  • S. Tan, L. Vandenberghe, J. Vandewalle, Remarks on the stability of asymmetric dynamical neural networks, Proceedings of the International Joint Conference on Neural Networks III461-III467, 1990.

  • L. Vandenberghe, J. Vandewalle, A globally convergent algorithm for solving a broad class of nonlinear resistive circuits, Proc. ISCAS, 403-406, 1990.

  • L. Vandenberghe, S. Tan, J. Vandewalle, Cellular neural networks: dynamic properties and adaptive learning algorithm. In: L.B. Almeida, C.J. Wellekens (Editors), Neural Networks, Proceedings of the EURASIP Workshop on Neural Networks, Sesimbra, Portugal, 141-150, Springer, 1990.

  • L. Vandenberghe, B. De Moor, J. Vandewalle, The generalized linear complementarity problem applied to the complete analysis of piecewise-linear resistive circuits, IEEE Transactions on Circuits and Systems CAS-36, 1382-1391, 1989.

  • M. Moonen, B. De Moor, L. Vandenberghe, J. Vandewalle, On- and off-line identification of linear state-space models, International Journal of Control 49, 219-232, 1989.

  • J. Vandewalle, L. Vandenberghe, M. Moonen, The impact of the singular value decomposition in system theory, signal processing, and circuit theory. In: H. Nijmeijer, J.M. Schumacher (Editors), Three Decades of Mathematical System Theory. A Collection of Surveys at the Occasion of the Fiftieth Birthday of Jan C. Willems, 453-479, Springer 1989.

  • L. Vandenberghe, J. Vandewalle, On the training and the convergence of brain-state-in-a-box neural networks. In: Proceedings of the First IEE Conference on Artificial Neural Networks, 247-251, 1989.

  • L. Vandenberghe, J. Vandewalle, Variable dimension algorithms for solving nonlinear resistive circuits, Proceedings of the European Conference on Circuit Theory and Design 385-389, 1989.

  • L. Vandenberghe, J. Vandewalle, Brain-state-in-a-box neural networks with asymmetric coefficients, Proceedings of the International Joint Conference on Neural Networks I627-I630, 1989.

  • L. Vandenberghe, J. Vandewalle, Dynamic properties of neural networks, Proceedings of the Tenth Symposium on Information Theory in the Benelux, 81-88, 1989.

  • L. Vandenberghe, B. De Moor, J. Vandewalle, The generalized linear complementarity problem applied to the complete analysis of resistive piecewise-linear circuits, Proc. ISCAS, 2155-2158, 1989.

  • B. De Moor, J. Vandewalle, M. Moonen, L. Vandenberghe, P. Van Mieghem, A geometrical strategy for the identification of linear multivariable systems with singular value decomposition, Identification and System Parameter Estimation 1988. Selected Papers from the Eighth IFAC/IFORS Symposium (Beijing, Aug. 1988), 1, 493-494, 1988.

  • B. De Moor, M. Moonen, L. Vandenberghe, J. Vandewalle, The application of the canonical correlation concept to the identification of linear state space models. In: A. Bensousan, J.L. Lions (Editors) Analysis and Optimization of Systems, 1103-1114, Springer, 1988.

  • B. De Moor, M. Moonen, L. Vandenberghe, J. Vandewalle, A geometrical approach for the identification of state space models with singular value decomposition, Proc. ICASSP, 2244-2247, 1988.

  • B. De Moor, M. Moonen, L. Vandenberghe, J. Vandewalle, Identification of linear state space models with singular value decomposition using canonical correlation concepts, In: E. Deprettere (Editor), Singular value decomposition and signal processing, 161-169, North-Holland, 1988.