Results 251 to 260 of about 789,696 (298)

Neural Predictors’ Sensitivity and Robustness

2021
The results of the application of deep neural predictors depend on a multitude of factors which compose the experimental settings. We report all the specific information to ensure the reproducibility of a wide number of numerical experiments. A sensitivity analysis on some critical aspects is provided in order to prove the robustness of our setting ...
M. Sangiorgio, F. Dercole, G. Guariso
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Sensitivity Analysis ofEAC's Robustness

The Engineering Economist, 1992
ABSTRACT Equivalent annuities are often used to compare mutually exclusive alternatives with unequal lives. This comparison assumes identical repetitions until a horizon equal to the least common multiple of the lives. Our paper examines the robustness of the equivalent annual cost (EAC) measure as the identical repetition assumption is violated ...
Ted G. Eschenbach, Alice E. Smith
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Robustness analysis using singular value sensitivities†

International Journal of Control, 1981
This paper introduces a linear time invariant system analysis tool, the singular value sensitivity function, which can be used in conjunction with singular value analyses to provide more complete estimates of system feedback properties. An important feature of this tool is the ability to analyze the effect of simultaneous variations in several system ...
J. Freudenberg, D. Looze, J. Cruz
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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.
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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 ...
Dupuis, Paul, James, Matthew R., Petersen, Ian   +2 more
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Robust SVM for Cost-Sensitive Learning

Neural Processing Letters, 2021
Although the performance of cost-sensitive support vector machine (CS-SVM) has been demonstrated to approximate to the cost-sensitive Bayes risk, previous CS-SVM methods still suffer from the influence of outlier samples and redundant features. Recently, a few studies have focused on separately solving these two issues by the sparse theory.
Jiangzhang Gan, Jiaye Li, Yangcai Xie
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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
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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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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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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
Fleming, Wendell H., McEneaney, William M.   +1 more
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