KFU. Card publication. Modelling of nonlinear filtering Poisson time series

KAZAN
FEDERAL UNIVERSITY

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MODELLING OF NONLINEAR FILTERING POISSON TIME SERIES

Form of presentation

Articles in international journals and collections

Year of publication

2016

Язык

английский

Authors, employees of KFU

Bochkarev Vladimir Vladimirovich, author

Bibliographic description in the original language

Bochkarev V.V, Belashova I.A., Modelling of nonlinear filtering Poisson time series//Journal of Physics: Conference Series. - 2016. - Vol.738, Is.1. - Art. № 012082.

Annotation

In this article, algorithms of non-linear filtering of Poisson time series are tested using statistical modelling. The objective is to find a representation of a time series as a wavelet series with a small number of non-linear coefficients, which allows distinguishing statistically significant details. There are well-known efficient algorithms of non-linear wavelet filtering for the case when the values of a time series have a normal distribution. However, if the distribution is not normal, good results can be expected using the maximum likelihood estimations. The filtration is studied according to the criterion of maximum likelihood by the example of Poisson time series. For direct optimisation of the likelihood function, different stochastic (genetic algorithms, annealing method) and deterministic optimization algorithms are used.

Keywords

nonlinear filtering, Poisson's distribution, maximul likelihood estimation

The name of the journal

Journal of Physics: Conference Series

URL

https://www.scopus.com/inward/record.uri?eid=2-s2.0-84988692831&partnerID=40&md5=250cec49edf11d7490a9b4103cffb304

Please use this ID to quote from or refer to the card

https://repository.kpfu.ru/eng/?p_id=166638&p_lang=2

Full metadata record

Field DC	Value	Language
dc.contributor.author	Bochkarev Vladimir Vladimirovich	ru_RU
dc.date.accessioned	2016-01-01T00:00:00Z	ru_RU
dc.date.available	2016-01-01T00:00:00Z	ru_RU
dc.date.issued	2016	ru_RU
dc.identifier.citation	Bochkarev V.V, Belashova I.A., Modelling of nonlinear filtering Poisson time series//Journal of Physics: Conference Series. - 2016. - Vol.738, Is.1. - Art. № 012082.	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=166638&p_lang=2	ru_RU
dc.description.abstract	Journal of Physics: Conference Series	ru_RU
dc.description.abstract	In this article, algorithms of non-linear filtering of Poisson time series are tested using statistical modelling. The objective is to find a representation of a time series as a wavelet series with a small number of non-linear coefficients, which allows distinguishing statistically significant details. There are well-known efficient algorithms of non-linear wavelet filtering for the case when the values of a time series have a normal distribution. However, if the distribution is not normal, good results can be expected using the maximum likelihood estimations. The filtration is studied according to the criterion of maximum likelihood by the example of Poisson time series. For direct optimisation of the likelihood function, different stochastic (genetic algorithms, annealing method) and deterministic optimization algorithms are used.	ru_RU
dc.language.iso	ru	ru_RU
dc.subject	nonlinear filtering	ru_RU
dc.subject	Poisson's distribution	ru_RU
dc.subject	maximul likelihood estimation	ru_RU
dc.title	Modelling of nonlinear filtering Poisson time series	ru_RU
dc.type	Articles in international journals and collections	ru_RU