Results 251 to 260 of about 2,734,080 (302)

Robust properties of risk-sensitive control

Proceedings of the 37th IEEE Conference on Decision and Control (Cat. No.98CH36171), 2000
The purpose of this paper is to characterize and prove robustness properties of risk-sensitive controllers precisely. The authors mainly presented the following two results: (1) explicit bounds of the average output power in terms of the input power, (2) a stochastic version of the small gain theorem, which is expressed in terms of the risk-sensitive ...
Paul Dupuis, Matthew R. James, Ian R. Petersen   +2 more
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SEU sensitivity of robust communication protocols

2012 IEEE 18th International On-Line Testing Symposium (IOLTS), 2012
Robust communications protocols are widely used in safety critical applications, such as aerospace or automotive systems. On-board complex systems, working in harsh environments, are composed of distributed modules with a high degree of interaction and critical tasks replication.
Celia López-Ongil, Marta Portela-García, Mario García-Valderas, Anna Vaskova, Luis Entrena, Joaquín Rivas-Abalo, Alberto Martín-Ortega, Javier Martinez-Oter, S. Rodriguez-Bustabad, Ignacio Arruego   +9 more
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Sensitivity and robustness of mechanism balancing

Mechanism and Machine Theory, 1998
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Sensitivity and Robustness in Chemical Reaction Networks

SIAM Journal on Applied Mathematics, 2009
For a wide class of chemical reaction networks, including all those governed by detailed balanced mass-action kinetics, we examine the robustness of equilibrium species concentrations against fluctuations in the overall reactant supply. In particular, we present lower bounds on the individual species-concentration sensitivities that derive from ...
Guy Shinar, Uri Alon 0001, Martin Feinberg   +2 more
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Sensitivity and robustness in selection problems

Computers & Operations Research, 2004
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Sensitivity and robustness of eigendecomposition-based detectors

IEEE International Conference on Acoustics Speech and Signal Processing, 1993
A new framework is presented for the analysis of the performance of detection methods, such as the Akaike's information criteria (AIC) and the minimum description length principle (MDL) which are based on the eigenvalues of the covariance matrix. It is shown that theoretical analysis of the probabilities of overestimation and underestimation can be ...
W. Xu, Mostafa Kaveh
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Robustness and sensitivity of biological models

Philosophical Studies, 2012
The aim of this paper is to develop ideas about robustness analyses. I introduce a form of robustness analysis that I call sufficient parameter robustness, which has been neglected in the literature. I claim that sufficient parameter robustness is different from derivational robustness, the focus of previous research.
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Sensitivity analysis of noise robustness methods

2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2004
The paper addresses the problem of noise robustness from the standpoint of the sensitivity to noise estimation errors. Since the noise is usually estimated in the power-spectral domain, we show that the implied error in the cepstral domain has interesting properties.
Luca Giulio Brayda, Luca Rigazio, Robert Boman, Jean-Claude Junqua   +3 more
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Robustness and Sensitivity of Network-Based Topic Detection

2023
In the context of textual analysis, network-based procedures for topic detection are gaining attention as an alternative to classical topic models. Network-based procedures are based on the idea that documents can be represented as word co-occurrence networks, where topics are defined as groups of strongly connected words. Although many works have used
Galluccio, C., Magnani, M., Vega, D., Ragozini, G., Petrucci, A.   +4 more
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Model-robust and model-sensitive designs

Computational Statistics & Data Analysis, 2005
The main drawback of the optimal design approach is that it assumes the statistical model is known. To overcome this problem, a new approach to reduce the dependency on the assumed model is proposed. The approach takes into account the model uncertainty by incorporating the bias in the design criterion and the ability to test for lack-of-fit.
Peter Goos, André Kobilinsky, Timothy E. O'Brien, Martina Vandebroek   +3 more
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