J. F. Sturm, "Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones." Optimization methods and software, vol. 11-12, no. 1-4, pp. 625--653, 1999, version 1.1 available from http://sedumi.mcmaster.ca/. Home/Search Document Not in Database Summary Related Articles Check |
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Interior Point Methods for Second-Order Cone Programming and.. - Kuo, Mittelmann (2003) (Correct)
....method and could probably handle larger sparse cases nearly as well as MOSEK. LOQO finally, is a general NLP code and it treats the SOCP problems as smoothed nondi#erentiable NLPs which in some cases leads to larger iteration counts. 22 Table 2: Comparison of our methods with the codes [1, 12, 14, 15] A. 4.4 A. 4.5 A.4.2 SeDu SDPT MOSK LOQO EX1 50 13 15 20 13 12 13 44 EX1 75 16 14 21 16 11 13 44 EX1 100 14 16 22 16 12 14 51 EX1 200 17 17 23 16 12 16 60 EX2 50 9 10 13 15 9 8 13 EX2 100 8 13 13 12 10 8 14 EX2 150 9 9 14 15 10 10 12 EX2 200 10 9 14 14 10 10 13 EX3 10 4 13 14 18 13 21 10 88 ....
Jos F. Sturm, "Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones," Optimization Methods and Software, 11/12 (1999), pp. 625--653.
Positive Polynomial Matrices and Improved LMI Robustness .. - Henrion, Arzelier.. (2002) (1 citation) (Correct)
....H(P ) 0: Proof: It is an application of the projection lemma, an algebraic result well known to the control community, see e.g. Skelton, 1998, Theorem 2.3.12] 2 4 Application to Robust Stability Analysis In all the following numerical examples we solved the LMI problems with SeDuMi 1. 04 [Sturm, 1999] running under Matlab 6.1 on a Sun Sparc Workstation Ultra 5. We notice that the LMI condition of Lemma 5 is simultaneously linear in coefficients of N(s) and in Lyapunov matrix P . This property can be exploited to provide less conservative convex conditions than the well known quadratic ....
J. F. Sturm "Using SeDuMi 1.02, a Matlab Toolbox for Optimization over Symmetric Cones", Optimization Methods and Software, Vol. 11-12, pp. 625--653, 1999. See also fewcal.kub.nl/sturm. 14
Discrete Robust SPR Design via Semidefinite Programming - Henrion (Correct)
....convex constraints on the controller coefficients can freely be incorporated, such as spectral or interpolation constraints on the controller dynamics. The simplicity and efficiency of the approach is illustrated on several numerical examples found in the literature, and a basic Matlab 1 SeDuMi [Sturm, 1999] implementation of the robust SPR design algorithm is given in the Appendix. A more sophisticated version of the design algorithm will be implemented into the next release 3.0 of the Polynomial Toolbox for Matlab [Polyx Ltd. 2001] 1 Matlab is a trademark of The MathWorks, Inc. 2 2 Main ....
.... frequently in control and signal processing [Vandenberghe, 1996] but also in convex relaxations to combinatorial optimization problems [Lasserre, 2001] Several user friendly packages have been developed to solve this convex optimization problem, such as the freeware SeDuMi interfaced with Matlab [Sturm, 1999]. In the next section, we show how robust SPR design problems can be solved in a matter of seconds with the help of this software. Before doing this, we will show that our approach is also suitable for solving the related problem of strengthened SPR design [Anderson, 1994] Corollary 1 Under the ....
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J. F. Sturm "Using SeDuMi 1.02, a Matlab Toolbox for Optimization over Symmetric Cones", Optimization Methods and Software, Vol. 11-12, pp. 625--653, 1999. See also fewcal.kub.nl/sturm.
Branch-and-Cut Algorithms for the Bilinear Matrix Inequality.. - Fukuda, al. (1999) (Correct)
....closely approximates F W . Replacing F W by such a set, the optimization problem becomes convex and therefore tractable [22] Moreover, if this set is described by linear inequalities, the convex relaxed problem becomes an SDP [32] and hence, efficiently solvable by currently available software [4, 9, 26, 28]. Goh et al. 14] proposed the (convex) polytope f G W to approximate F W : f G W = x ; y ; W ) 2 IR n 2 IR m 2 IR n2m : x ; y) 2 H; w ij w ij w ij ; i 2 I n ; j 2 J m ) where w ij = minfx i y j ; x i y j ; x i y j ; x i y j g w ij = maxfx i y j ; x i y j ; x i y j ; ....
....The convex relaxations and the algorithms exposed here can be naturally extended to optimization problems with a bilinear objective function and BMI constraints. On the contrary of the BMIEPs which are always feasible, these problems can be infeasible. However, the currently available SDP packages [9, 26, 28] can detect infeasibility of the SDPs, and therefore, only minor modifications are necessary in the proposed algorithms to solve these problems. A different approach to solve problems involving BMIs was recently proposed by Kojima and Tun cel. They announced two conceptual algorithms based on LP ....
J. F. Sturm, "Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones," Department of Quantitative Economics, Maastricht University, Maastricht, The Netherlands, August 1998. Available at http://www.unimaas.nl/~sturm/software/sedumi.html.
Security of Lattice-Based Data Hiding Against the - Known Message Attack (Correct)
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J. F. Sturm, "Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones." Optimization methods and software, vol. 11-12, no. 1-4, pp. 625--653, 1999, version 1.1 available from http://sedumi.mcmaster.ca/.
A Sparse Signal Reconstruction Perspective for . . . - Malioutov (2003) (Correct)
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J. S. Sturm, "Using SeDuMi 1.02, a Matlab toolbox for optimization over symmetric cones," Tech. Rep., Tilburg University, Department of Econometrics, Netherlands, 2001, http://fewcal.kub.nl/ sturm.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 5.. - Wireless Networking.. (Correct)
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F. Sturm, "Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones," Optimization Methods and Software, 11-12 (1999), pp. 625-653, Special issue on Interior Point Methods (CD supplement with software).
Unknown - (Correct)
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J. F. Sturm, "Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones," Optim. Methods and Softw. 11--12 (1999) 625--653. Available at http://fewcal.kub.nl/sturm/software/sedumi.html.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS (TO APPEAR) 1 .. - Networking Adapted To (Correct)
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F. Sturm, "Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones," Optimization Methods and Software, 11-12 (1999) 625-653. Special issue on Interior Point Methods (CD supplement with software).
A Near Maximum Likelihood Decoding Algorithm for.. - Mobasher.. (2005) (Correct)
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J. Sturm, "Using sedumi 1.02, a matlab toolbox for optimization over symmetric cones," Optimization Methods and Software, vol. 11-12, pp. 625--653, 1999.
A Near Maximum Likelihood Decoding Algorithm for.. - Mobasher.. (2005) (Correct)
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J. Sturm, "Using sedumi 1.02, a matlab toolbox for optimization over symmetric cones," Optimization Methods and Software, vol. 11-12, pp. 625--653, 1999.
A Near Maximum Likelihood Decoding Algorithm for.. - Mobasher.. (2005) (Correct)
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J. Sturm, "Using sedumi 1.02, a matlab toolbox for optimization over symmetric cones," Optimization Methods and Software, vol. 11-12, pp. 625--653, 1999.
Source Localization By Enforcing Sparsity Through A Laplacian - Prior An Svd-Based (Correct)
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J. S. Sturm, "Using SeDuMi 1.02, a Matlab toolbox for optimization over symmetric cones," Tech. Rep., Tilburg To obtain this plot, we have used the adaptive grid refinement approach from Section 5 to get point estimates not limited to the grid.
Linear precoding via conic optimization for fixed MIMO.. - Wiesel, Eldar, (Shitz) (2004) (Correct)
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J. F. Sturm, "Using SEDUMI 1.02, a Matlab toolbox for optimizations over symmetric cones," Optimization Meth. and Soft., vol. 11-12, 1999.
Blind Equalization Of Constant Modulus Signals Via Restricted - Convex Optimization Boris (Correct)
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J. F. Sturm, "Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones," Optim. Meth. Software, vol. 11--12, pp. 625--653, 1999. Also: http://www. unimaas.nl/sturm/software/sedumi.html.
Multiuser Precoders for Fixed Receivers - Ami Wiesel Yonina (2004) (Correct)
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J. F. Sturm, "Using SEDUMI 1.02, a Matlab toolbox for optimizations over symmetric cones," Optimization Meth. and Soft., vol. 11-12, 1999.
User's Guide for SEDUMI INTERFACE 1.04 - Dimitri Peaucelle Didier (Correct)
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J.F. STURM, "Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones", Optimization Methods and Software, vol. 11-12, 1999, pages 625-653, URL: fewcal.kub.nl /sturm/software/sedumi.html.
Lagrangian Dual Interior-Point Methods for Semidefinite Programs - Fukuda, al. (2001) (1 citation) (Correct)
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J. F. Sturm, "Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones," Optim. Methods and Softw. 11--12 (1999) 625--653. Available at http://fewcal.kub.nl/sturm/software/sedumi.html.
Interior-Point Methods for Lagrangian Duals of Semidefinite.. - Fukuda, Kojima (2000) (2 citations) (Correct)
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J. F. Sturm, "Using SeDuMi 1.02, MATLAB toolbox for optimization over symmetric cones," Optim. Methods and Software 11--12 (1999) 625--653.
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