Results 21 to 30 of about 1,437,172 (250)
Ruin Probability Approximations in Sparre Andersen Models with Completely Monotone Claims
Risks, 2019 We consider the Sparre Andersen risk process with interclaim times that belong to the class of distributions with rational Laplace transform. We construct error bounds for the ruin probability based on the Pollaczek−Khintchine formula, and develop ...
Hansjörg Albrecher, Eleni Vatamidou
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Sound Over-Approximation of Probabilities
Acta Cybernetica, 2020 Safety analysis of high confidence systems requires guaranteed bounds on the probability of events of interest. Establishing the correctness of algorithms that compute such bounds is challenging. We address this problem in three steps. First, we use monadic transition systems (MTS) in the category of sets as a general framework for modeling discrete ...
Eugenio Moggi +2 more
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Безопасность информационных технологий, 2021 ARX stochastic algorithms are a promising solution in the development of unpredictable pseudo- random number generators for low-resource systems. The ease of implementation of their round operations, as well as their high energy efficiency, make the ...
Alexander A. Kozlov, Mikhail A. Ivanov
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Probabilistic Output Analyses for Deterministic Programs — Reusing Existing Non-probabilistic Analyses [PDF]
Electronic Proceedings in Theoretical Computer Science, 2020 We consider reusing established non-probabilistic output analyses (either forward or backwards) that yield over-approximations of a program's pre-image or image relation, e.g., interval analyses. We assume a probability measure over the program input and
Maja Hanne Kirkeby
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Explicitly Invertible Approximations of the Gaussian Q-Function: A Survey
IEEE Open Journal of the Communications Society, 2023 Communications and information theory use the Gaussian $Q$ -function, a positive and decreasing function, across the literature. Its approximations were created to simplify mathematical study of the Gaussian $Q$ -function expressions. This is important
Alessandro Soranzo +4 more
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Scarce Sample-Based Reliability Estimation and Optimization Using Importance Sampling
Mathematical and Computational Applications, 2022 Importance sampling is a variance reduction technique that is used to improve the efficiency of Monte Carlo estimation. Importance sampling uses the trick of sampling from a distribution, which is located around the zone of interest of the primary ...
Kiran Pannerselvam +2 more
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AppliedMath, 2022 We consider the inhomogeneous Wiener–Hopf equation whose kernel is a nonarithmetic probability distribution with positive mean. The inhomogeneous term behaves like a submultiplicative function.
Mikhail Sgibnev
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Impact of Antenna Correlation on a New Dual-Hop MIMO AF Relaying Model
EURASIP Journal on Wireless Communications and Networking, 2010 A novel system model is proposed for the dual-hop multiple-input multiple-output amplify-andforward relay networks, and the impact of antenna correlation on the performance is studied.
Gayan Amarasuriya +2 more
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Parallel probability density approximation [PDF]
Behavior Research Methods, 2019 Probability density approximation (PDA) is a nonparametric method of calculating probability densities. When integrated into Bayesian estimation, it allows researchers to fit psychological processes for which analytic probability functions are unavailable, significantly expanding the scope of theories that can be quantitatively tested. PDA is, however,
Yi-Shin, Lin +2 more
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A logic-based tractable approximation of probability
Journal of Logic and Computation, 2022 AbstractWe provide a logical framework in which a resource-bounded agent can be seen to perform approximations of probabilistic reasoning. Our main results read as follows. First, we identify the conditions under which propositional probability functions can be approximated by a hierarchy of depth-bounded belief functions.
Paolo Baldi, Hykel Hosni
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