Results 281 to 290 of about 822,275 (310)

Linear Equations and Linear Inequalities

2002
While Chapter 1 reviews general structural aspects of real vector spaces, we now discuss fundamental computational techniques for linear systems in this chapter. For convenience of the discussion, we generally assume that the coefficients of the linear systems are real numbers.
Ulrich Faigle, Walter Kern, Georg Still
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Positivity and Linear Matrix Inequalities

European Journal of Control, 2002
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Genin, Y., Hachez, Y., Nesterov, Yu., Ştefan, R., Van Dooren, P., Xu, S.   +5 more
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Linear Inequalities Over Complex Cones

Canadian Mathematical Bulletin, 1973
The basic solvability theorems of Farkas [2] and Levinson [4] were recently extended in different directions by Ben-Israel [1] and Kaul [3].The theorem stated in this note generalizes both results of Ben-Israel and Kaul and is applicable to nonlinear programming over complex cones.
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Convex Matrix Inequalities Versus Linear Matrix Inequalities

IEEE Transactions on Automatic Control, 2009
Most linear control problems lead directly to matrix inequalities (MIs). Many of these are badly behaved but a classical core of problems are expressible as linear matrix inequalities (LMIs). In many engineering systems problems convexity has all of the advantages of a LMI. Since LMIs have a structure which is seemingly much more rigid than convex MIs,
J.W. Helton, S. McCullough, M. Putinar, V. Vinnikov   +3 more
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Linear inequalities for covering codes. II. Triple covering inequalities

IEEE Transactions on Information Theory, 1992
Summary: The linear inequality method for covering codes is generalized. This method reduces the study of covering codes to the study of some local covering problems. One of these problems, the so-called 1-3 covering system, is formulated and studied in detail.
Zhang, Zhen, Lo, Chiaming
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Linear Matrix Inequalities in Control

2007
This chapter gives an introduction to the use of linear matrix inequalities (LMIs) in control. LMI problems are defined and tools described for transforming matrix inequality problems into a suitable LMI-format for solution. Several examples explain the use of these fundamental tools.
Herrmann, G, Turner, MC, Postlethwaite, I   +2 more
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Linear Matrix Inequalities

2011
The origin of Linear Matrix Inequalities (LMIs) goes back as far as 1890, although they were not called this way at that time, when Lyapunov showed that the stability of a linear system \( {\bf {\dot x}} = {\bf {Ax}} \) is equivalent to the existence of a positive definite matrix P, which satisfies the matrix inequality\( \bf {{A^T}P} + \bf {PA} < \bf {
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Linear Inequalities

1978
Murray C. Kemp, Yoshio Kimura
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Linear inequality

2001
Saul I. Gass, Carl M. Harris
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Linear Conformable Inequalities

2020
Douglas R. Anderson, Svetlin G. Georgiev
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