Results 261 to 270 of about 361,200 (307)

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
openaire   +1 more source

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 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
openaire   +3 more sources

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
openaire   +3 more sources

Risk-Sensitive and Robust Escape Criteria

SIAM Journal on Control and Optimization, 1997
Abstract: "The problem of controlling a noisy process so as to prevent it from leaving a prescribed set has a number of interesting applications. In this paper, new criteria for this problem are considered. First, a risk-sensitive criterion for a stochastic diffusion process model is examined, and it is shown that the value is a classical solution of a
Dupuis, Paul, McEneaney, William M.
openaire   +2 more sources

Robust Designs Through Risk Sensitivity: An Overview

Journal of Systems Science and Complexity, 2021
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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A Robust and Sensitive Metric for Quantifying Movement Smoothness

IEEE Transactions on Biomedical Engineering, 2012
The need for movement smoothness quantification to assess motor learning and recovery has resulted in various measures that look at different aspects of a movement's profile. This paper first shows that most of the previously published smoothness measures lack validity, consistency, sensitivity, or robustness.
Sivakumar Balasubramanian, Alejandro Melendez-Calderon, Etienne Burdet   +2 more
openaire   +5 more sources

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
openaire   +1 more source

Robust Limits of Risk Sensitive Nonlinear Filters

Mathematics of Control, Signals, and Systems, 2001
This paper deals with deterministic and stochastic (risk sensitive) nonlinear filters. In the first part, the following deterministic filter model is considered: state equation, \(\dot x_t=f(x_t)+ \sigma(x_t) w_t\), and (accumulated) observation, \(\dot y_t=h(x_t)+v_t\), where \(w_t\) and \(v_t\) are deterministic disturbances. Applying the mean square
Wendell H. Fleming, William M. McEneaney
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Stability, Sensitivity and Robustness

2010
We are interested in the dynamic behavior of systems, more particularly we are interested in changing the behavior of a system, but before we attempt to synthesize desired behavior it pays to analyze system properties.
Pedro Albertos, Iven Mareels
openaire   +1 more source