KFU. Card publication. IDENTIFICATION ALGORITHMS OF SIMPLE HOMOGENEOUS MARKOV CHAINS OF CYCLIC CLASS AND THEIR COMPLEXITY ANALYSIS

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IDENTIFICATION ALGORITHMS OF SIMPLE HOMOGENEOUS MARKOV CHAINS OF CYCLIC CLASS AND THEIR COMPLEXITY ANALYSIS

Form of presentation

Articles in international journals and collections

Year of publication

2016

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Authors, employees of KFU

Nurutdinova Alsu Rafailovna, author

Bibliographic description in the original language

IDENTIFICATION ALGORITHMS OF SIMPLE HOMOGENEOUS MARKOV CHAINS OF CYCLIC CLASS AND THEIR COMPLEXITY ANALYSIS. Nurutdinova A.R., Shalagin S.V.// International Journal of Pharmacy & Technology.-2016.-�3.-P. 18926-18935.

Annotation

The homogeneous regular and cyclic Markov chains (MC) are widely used in modelling systems for real stochastic processes, events and phenomena. In particular, the sequence recognition tasks for the MCs generated on the basis of the ergodic stochastic matrices (ESMs) are of interest. These tasks are relevant and applicable to processing of any digital signal sequences, analyzing and testing of any discrete devices, identifying of any spoken and written language. As part of the task of the discrete Markov processes analyzing, there is a problem of effective recognition methods and algorithms choice depending on the investigated model parameters, in particular, length of the output sequence, stochastic matrix dimension and structure, and accuracy of representation of such model elements. In order to address this issue, this article proposes methods and algorithms for identifying various subclasses of the automate Markov model based on the generated cyclic Markov chains.

Keywords

cyclic Markov chains

The name of the journal

International journal of pharmacy & technology

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

https://repository.kpfu.ru/eng/?p_id=141820&p_lang=2

Full metadata record

Field DC	Value	Language
dc.contributor.author	Nurutdinova Alsu Rafailovna	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	IDENTIFICATION ALGORITHMS OF SIMPLE HOMOGENEOUS MARKOV CHAINS OF CYCLIC CLASS AND THEIR COMPLEXITY ANALYSIS. Nurutdinova A.R., Shalagin S.V.// International Journal of Pharmacy & Technology.-2016.-�3.-P. 18926-18935.	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=141820&p_lang=2	ru_RU
dc.description.abstract	International journal of pharmacy & technology	ru_RU
dc.description.abstract	The homogeneous regular and cyclic Markov chains (MC) are widely used in modelling systems for real stochastic processes, events and phenomena. In particular, the sequence recognition tasks for the MCs generated on the basis of the ergodic stochastic matrices (ESMs) are of interest. These tasks are relevant and applicable to processing of any digital signal sequences, analyzing and testing of any discrete devices, identifying of any spoken and written language. As part of the task of the discrete Markov processes analyzing, there is a problem of effective recognition methods and algorithms choice depending on the investigated model parameters, in particular, length of the output sequence, stochastic matrix dimension and structure, and accuracy of representation of such model elements. In order to address this issue, this article proposes methods and algorithms for identifying various subclasses of the automate Markov model based on the generated cyclic Markov chains.	ru_RU
dc.language.iso	ru	ru_RU
dc.subject		ru_RU
dc.title	IDENTIFICATION ALGORITHMS OF SIMPLE HOMOGENEOUS MARKOV CHAINS OF CYCLIC CLASS AND THEIR COMPLEXITY ANALYSIS	ru_RU
dc.type	Articles in international journals and collections	ru_RU