Importance Sampling for Failure Probabilities in Computing and Data Transmission
نویسندگان
چکیده
منابع مشابه
Importance Sampling for Failure Probabilities in Computing and Data Transmission
In this paper we study efficient simulation algorithms for estimating P(X > x), whereX is the total time of a job with ideal time T that needs to be restarted after a failure. The main tool is importance sampling, where a good importance distribution is identified via an asymptotic description of the conditional distribution of T given X > x. If T ≡ t is constant, the problem reduces to the eff...
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Abstaract. A novel simulation approach, called Adaptive Linked Importance Sampling (ALIS), is proposed to compute small failure probabilities encountered in high-dimensional reliability analysis of engineering systems. It was shown by Au and Beck (2003) that Importance Sampling (IS) does generally not work in high dimensions. A geometric understanding of why this is true when one uses a fixed i...
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An iterative method for estimating the failure probability for certain time-variant reliability problems has been developed. In the paper, the focus is on the displacement response of a linear oscillator driven by white noise. Failure is then assumed to occur when the displacement response exceeds a critical threshold. The iteration procedure is a two-step method. On the first iteration, a simp...
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The researcher faced with a computationally intensive simulation will either seek powerful processing capabilities or turn to variance reduction techniques. In many situations, a combination of both approaches is required to achieve the desired accuracy. In the study of rare events, importance sampling (IS) is the only variance reduction technique which has been shown to offer the potential for...
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We propose and analyze a method for computing failure probabilities of systems modeled as numerical deterministic models (e.g., PDEs) with uncertain input data. A failure occurs when a functional of the solution to the model is below (or above) some critical value. By combining recent results on quantile estimation and the multilevel Monte Carlo method we develop a method which reduces computat...
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ژورنال
عنوان ژورنال: Journal of Applied Probability
سال: 2009
ISSN: 0021-9002,1475-6072
DOI: 10.1239/jap/1253279851