Results 11 to 20 of about 16,041 (196)
Multivariate Bernoulli and Euler polynomials via Lévy processes [PDF]
Applied Mathematics Letters, 2012 By a symbolic method, we introduce multivariate Bernoulli and Euler polynomials as powers of polynomials whose coefficients involve multivariate L vy processes. Many properties of these polynomials are stated straightforwardly thanks to this representation, which could be easily implemented in any symbolic manipulation system.
Elvira Di Nardo, Immacolata Oliva
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Application of Bernoulli Process-Based Charts to Electronic Assembly
International Journal of Engineering Business Management, 2015 The application of protective gel, which is a subprocess of the electronic assembly of the exhaust gas recirculation sensor, is a highly capable process with the fraction of nonconforming units as low as 200 ppm. Every unit is inspected immediately after
Darja Noskievičová +2 more
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IEEE Access, 2018 The cardinality-balanced multi-target multi-Bernoulli (CBMeMBer) filter is a promising solution for multi-target tracking. However, the performance of the CBMeMBer filter will be degraded severely by outliers in the presence of heavy-tailed process noise
Mingjie Wang +3 more
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Strong approximation of very weak Bernoulli processes [PDF]
Zeitschrift f�r Wahrscheinlichkeitstheorie und Verwandte Gebiete, 1983 Very weak Bernoulli processes with values in a separable metric space are introduced. An estimate for the Prohorov distance in the central limit theorem is obtained. This estimate is used to establish a strong (almost sure) approximation of the partial sums of a very weak Bernoulli process by a Brownian motion where the error term is of the order O(t1 ...
Ernst Eberlein
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Improving Machine Learning Performance by Eliminating the Influence of Unclean Data [PDF]
Engineering and Technology Journal, 2022 Regardless of the data source and type (text, digital, photo group, etc.), they are usually unclean data. The term (unclean) means that data contains some bugs and paradoxes that can strongly impact machine learning processes.
Murtadha Ressan, Rehab Hassan
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Imprecise Bernoulli Processes [PDF]
, 2012 In classical Bernoulli processes, it is assumed that a single Bernoulli experiment can be described by a precise and precisely known probability distribution. However, both of these assumptions can be relaxed. A first approach, often used in sensitivity analysis, is to drop only the second assumption: one assumes the existence of a precise distribution,
De Bock, Jasper, de Cooman, Gert
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Generalized Bernoulli process with long-range dependence and fractional binomial distribution
Dependence Modeling, 2021 Bernoulli process is a finite or infinite sequence of independent binary variables, Xi, i = 1, 2, · · ·, whose outcome is either 1 or 0 with probability P(Xi = 1) = p, P(Xi = 0) = 1 – p, for a fixed constant p ∈ (0, 1).
Lee Jeonghwa
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Bernoulli Filters for Multiple Correlated Sensors
IEEE Access, 2021 The Bernoulli filter is a general, Bayes-optimal solution for tracking a single disappearing and reappearing target, using a single sensor whose observations are corrupted by missed detections and a general, known clutter process.
Ronald Mahler
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The Beta-Bernoulli process and algebraic effects
, 2018 In this paper we use the framework of algebraic effects from programming language theory to analyze the Beta-Bernoulli process, a standard building block in Bayesian models. Our analysis reveals the importance of abstract data types, and two types of program equations, called commutativity and discardability.
Sam Staton +5 more
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Quantum channel measurement with local quantum Bernoulli noises
Scientific Reports, 2022 As an important stochastic process, quantum Bernoulli noises has a very important physical background and is an important research object in the field of quantum information.
Qi Han, Yanan Han, Yaxin Kou, Ning Bai
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