Zobrazeno 1 - 10
of 850
pro vyhledávání: '"nonparametric Bayesian"'
Autor:
M. I. Bogachev, K. R. Grigarevichius, N. S. Pyko, S. A. Pyko, M. Tsygankova, E. A. Plotnikova, T. V. Ageeva, Ya. O. Mukhamedshina
Publikováno v:
Известия высших учебных заведений России: Радиоэлектроника, Vol 27, Iss 3, Pp 108-123 (2024)
Introduction. Analysis of locomotor activity is essential in a number of biomedical and pharmacological research designs, as well as environmental monitoring. The movement trajectories of biological objects can be represented by time series exhibitin
Externí odkaz:
https://doaj.org/article/d5c83db573144538ad2b8f8224f5bf77
Publikováno v:
AIMS Mathematics, Vol 9, Iss 7, Pp 18103-18116 (2024)
In many applications, modeling based on a normal kernel is preferred because not only does the normal kernel belong to the family of stable distributions, but also it is easy to satisfy the stationary condition in the stochastic process. However, the
Externí odkaz:
https://doaj.org/article/e839f8538d64429cb1bd5a87116486df
Autor:
Nikita S. Pyko, Denis V. Tishin, Pavel Yu. Iskandirov, Artur M. Gafurov, Bulat M. Usmanov, Mikhail I. Bogachev
Publikováno v:
Известия высших учебных заведений России: Радиоэлектроника, Vol 26, Iss 3, Pp 32-47 (2023)
Introduction. Nonparametric Bayesian networks are a promising tool for analyzing, visualizing, interpreting and predicting the structural and dynamic characteristics of complex systems. Modern interdisciplinary research involves the complex processin
Externí odkaz:
https://doaj.org/article/0963cc8e7728450a8f66f5912a4ea7a2
Akademický článek
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Autor:
Nandram, Balgobin, Liu, Yang
Publikováno v:
Statistics in Transition. New Series. 23(4):21-36
Externí odkaz:
https://www.ceeol.com/search/article-detail?id=1096937
Publikováno v:
Journal of Statistical Software, Vol 102, Pp 1-36 (2022)
Gaussian processes are a class of flexible nonparametric Bayesian tools that are widely used across the sciences, and in industry, to model complex data sources. Key to applying Gaussian process models is the availability of well-developed open sourc
Externí odkaz:
https://doaj.org/article/cecd991415854fcf8c5440cd72a9727f
Publikováno v:
Applied Sciences, Vol 14, Iss 1, p 306 (2023)
Among the numerous techniques followed to learn a linear classifier through the discriminative dictionary and sparse representations learning of signals, the techniques to learn a nonparametric Bayesian classifier jointly and discriminately with the
Externí odkaz:
https://doaj.org/article/31c2efa5dd07495ca6cb2d1862c25a76
Autor:
Daobo Yan, Yi Xiong, Zhihong Zhan, Xiaohong Liao, Fangchao Ke, Hailiang Lu, Yulun Ren, Shuang Liao, Lipin Sun, Qixin Wang
Publikováno v:
Energy Reports, Vol 7, Iss , Pp 990-997 (2021)
This paper presents a set of nonparametric methods for selecting credit evaluation indicators under the condition of unknown index distribution, and applies the data of four power companies as samples for application analysis. The results show that t
Externí odkaz:
https://doaj.org/article/8c584535ea78447fb14435b758a6d7f6
Akademický článek
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Publikováno v:
IEEE Access, Vol 8, Pp 118114-118124 (2020)
Underground pipeline mapping is important in urban construction. There are few specific procedures and approaches to map underground pipelines using ground penetration radar (GPR) without knowing the number of buried pipelines. In this paper, an auto
Externí odkaz:
https://doaj.org/article/a579c5242706470793f22d241168234e