Results 271 to 280 of about 20,081 (298)

An alternative characterization of the structured singular value

Proceedings of 1994 33rd IEEE Conference on Decision and Control, 2002
The size of the smallest, structured, destabilizing perturbation for a linear, time-invariant, system can be calculated via the structured singular value (/spl mu/). It can be bounded above by the solution of a linear matrix inequality (LMI). This paper gives an alternative characterization which is particularly suited to the case when the system (or ...
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Computation of the real structured singular value

Guidance, Navigation and Control Conference, 1989
For a large class of linear time-invariant systems with real parametric perturbations, the coefficient vector of the characteristic polynomial is a multilinear function of the real parameter vector. Based on this multilinear mapping relationship together with the recent developments for wlvtmic wlvnomials and Darameter domain partitioning tkchnique ...
B.-C. CHANG, O. EKDAL, H.H. YEH, S. BANDA   +3 more
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Upper bounds of structured singular values for mixed uncertainties

42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475), 2004
Upper bounds of structured singular values for mixed uncertainties whose computations are efficient and reliable have been available. For uncertainties without real blocks and repeated complex scalar blocks, existing upper bounds are known to be quite tight.
Jietae Lee, Thomas F. Edgar
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Improved upper bounds for the mixed structured singular value

IEEE Transactions on Automatic Control, 1997
The authors consider the structured singular value \(\mu_K(M)\) of a complex \(n\times n\) matrix \(M\) with respect to some block structure \(K\) that defines the perturbation matrix \(\Delta\). \[ \mu_K(M)= \min_{\Delta\in\chi} \{\overline\sigma(\Delta),\text{ det}(I-\Delta M)= 0\}, \] \(\chi\) being a class of block diagonal matrices defined by \(K\)
Minyue Fu 0001, Nikita Barabanov
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Continuity properties of the real/complex structured singular value

IEEE Transactions on Automatic Control, 1993
Summary: The structured singular-value function \((\mu)\) is defined with respect to a given uncertainty set. This function is continuous if the uncertainties are allowed to be complex. However, if some uncertainties are required to be real, then it can be discontinuous.
Andrew K. Packard, Pradeep Pandey
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A new upper bound for the real structured singular value

Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228), 2002
A new, easily computable, upper bound on the real structured singular value /spl mu/ is derived under the assumption of a nonrepeated largest singular value. The condition under which real /spl mu/ is (strictly) less than the largest singular value is used to embed the structured uncertainty set in a larger related set.
S. K. Gungah, Umar Malik, Imad M. Jaimoukha, George D. Halikias   +3 more
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An upper bound of structured singular value

International Journal of Control, Automation and Systems, 2009
An improved upper bound of structured singular value for mixed uncertainties with purely real uncertainty blocks is proposed.
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Extensions to the structured singular value

1999
NOTE: Text or symbols not renderable in plain ASCII are indicated by [...]. Abstract is included in .pdf document. There are two basic approaches to robustness analysis. The first is Monte Carlo analysis which randomly samples parameter space to generate a profile for the typical behavior of the system.
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Phase-sensitive structured singular value

1999
Given Γ ∈ C n ×n with Γ + Γ* ≥ 0, define the phase Φ(Γ) of Γ by $$\Phi \left( \Gamma \right) = {\cot ^{ - 1}}\left( {\sup \left\{ {b:\Gamma + \Gamma * - \frac{\beta }{j}\left( {\Gamma - \Gamma *} \right) \geqslant 0\forall \beta \in \left\{ { - b,\,b} \right\}} \right\}} \right).$$
André L. Tits, V. Balakrishnan
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Fast Multilinear Singular Value Decomposition for Structured Tensors

SIAM Journal on Matrix Analysis and Applications, 2008
The higher-order singular value decomposition (HOSVD) is a generalization of the singular value decomposition (SVD) to higher-order tensors (i.e., arrays with more than two indices) and plays an important role in various domains. Unfortunately, this decomposition is computationally demanding.
Roland Badeau, Rémy Boyer
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