Modeling of data acquisition systems using the queueing theory

Modeling of data acquisition systems using the queueing theory

Mostra altre versioni (1)

This paper describes the features of a data acquisition system modeling based on queueing theory method. The main elements of the studied data acquisition system structure are sample hold amplifiers and dual-slope analogue digital converters. In case of the threshold control of technological facilit...

Descrizione completa

Salvato in:

Dettagli Bibliografici
Autori principali:	Fedorenko, V. V., Федоренко, В. В.
Natura:	Статья
Lingua:	English
Pubblicazione:	Elsevier GmbH 2018
Soggetti:	Analogue digital converter Data acquisition system Markov model Queueing theory Data acquisition
Accesso online:	https://www.scopus.com/record/display.uri?eid=2-s2.0-85015253990&origin=resultslist&sort=plf-f&src=s&st1=Modeling+of+data+acquisition+systems+using+the+queueing+theory&st2=&sid=97089f1e058ec08e3dec0b149bd56c66&sot=b&sdt=b&sl=77&s=TITLE-ABS-KEY%28Modeling+of+data+acquisition+systems+using+the+queueing+theory%29&relpos=4&citeCnt=3&searchTerm=# https://dspace.ncfu.ru/handle/20.500.12258/3052
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne! !

Documenti analoghi

Modeling of data acquisition systems using the queueing theory
di: Fedorenko, V. V., et al.
Pubblicazione: (2018)

A model of two-stage polling in alarm data acquisition system
di: Fedorenko, V. V., et al.
Pubblicazione: (2020)

Persistent short time series data acquisition algorithm for wireless smart sensor networks
di: Tebueva, F. B., et al.
Pubblicazione: (2018)

The modeling of mineral water fields data structure
di: Makarova, A. A., et al.
Pubblicazione: (2021)

Mobile Laboratory for Identification of Radial Distribution Network Topology
di: Zelensky, E. G., et al.
Pubblicazione: (2023)

Impact of mergers and acquisitions on companies’ financial performance
di: Panaedova, G. I., et al.
Pubblicazione: (2020)

A reliable method of wireless communication of robotic systems based on data threshold separation
di: Kocherov, Y. N., et al.
Pubblicazione: (2022)

Application of Common Information Models for integration of rural electric networks information systems
di: Efanov, A. V., et al.
Pubblicazione: (2023)

Mathematical modelling of the process for impact on automated information system security of threats access to restricted information
di: Rosenko, A. P., et al.
Pubblicazione: (2018)

Mathematical modelling of the process for impact on automated information system security of threats access to restricted information
di: Rosenko, A. P., et al.
Pubblicazione: (2018)

Safe storage of biometric data
di: Kocherov, Y. N., et al.
Pubblicazione: (2021)

Big Data study aid
di: Cheremukhin, A. D.

Opportunities and challenges in deep generative models
di: Nikolaev, E. I., et al.
Pubblicazione: (2019)

Comparative Analysis of Methods and Algorithms for Building a Digital Twin of a Smart City
di: Lutsenko, V. V., et al.
Pubblicazione: (2023)

Bayesian decision making using partial data for fractured poroelastic media
di: Tyrylgin, A. A., et al.
Pubblicazione: (2024)

Positional characteristics for efficient number comparison over the homomorphic encryption
di: Babenko, M. G., et al.
Pubblicazione: (2020)

Comparative performance analysis of information dispersal methods
di: Deryabin, M. A., et al.
Pubblicazione: (2019)

The use of redundant modular codes for improving the fault tolerance of special processors for digital signal processing
di: Makarova, A. V., et al.
Pubblicazione: (2018)

The use of redundant modular codes for improving the fault tolerance of special processors for digital signal processing
di: Makarova, A. V., et al.
Pubblicazione: (2018)

Neural network system for analyzing statistical factors of patients for predicting the survival of dental implants
di: Lyakhov, P. A., et al.
Pubblicazione: (2023)

A computational theory for the model construction, inspection and variation phase in human spatial reasoning
di: Holldobler, S.
Pubblicazione: (2020)

Legal features of the use of big data in the financial activities of the state
di: Smirnov, D. A., et al.
Pubblicazione: (2021)

Industrial systems management in the context of digital transformation
di: Khubulova, V. V., et al.
Pubblicazione: (2021)

Designing forward converters for data transmission systems in two-level RNS
di: Bergerman, M. V., et al.
Pubblicazione: (2019)

A mathematical model of load distribution for data center server clusters
di: Mochalov, V. P., et al.
Pubblicazione: (2021)

Digital pedagogy: tools and services in the work of a teacher study aid
di: Toktarova, V. I.

Architecture development of cloud-based fail-safe privacy data storage and processing system
di: Kucherov, N. N., et al.
Pubblicazione: (2020)

Towards optimizing cloud computing using residue number system
di: Kucherov, N. N., et al.
Pubblicazione: (2021)

Legal features of the use of big data in the tax activities of the state
di: Smirnov, D. A., et al.
Pubblicazione: (2022)

Fragmentation of data packets in wireless sensor network with variable temperature and channel conditions
di: Fedorenko, V. V., et al.
Pubblicazione: (2024)

Digital technologies in the financial sector: Evolution and major development trends in Russia and Abroad
di: Zenchenko, S. V., et al.
Pubblicazione: (2021)

Role of Red data book in conservation of biodiversity in Stavropol territory
di: Pushkin, S. V., et al.
Pubblicazione: (2019)

Models of integrity assurance in big relational databases
di: Malikov, A. V., et al.
Pubblicazione: (2018)

Models of integrity assurance in big relational databases
di: Malikov, A. V., et al.
Pubblicazione: (2018)

Modeling the recipe composition of food products and recommendations for their use in individual nutrition
di: Sadovoy, V. V., et al.
Pubblicazione: (2021)

Bi-objective analysis of an adaptive secure data storage in a multi-cloud
di: Babenko, M. G., et al.
Pubblicazione: (2019)

Работа с сервисом бизнес-аналитики Yandex DataLens учебное пособие
di: Березовская, Е. А.

A Dynamic Load Balancing Method for Data Centers with Fractal Properties of Network Traffic
di: Mochalov, V. P., et al.
Pubblicazione: (2022)

The identification of data anomalies from information sensors based on the estimation of the correlation dimension of the time series attractor in situational management systems
di: Tebueva, F. B., et al.
Pubblicazione: (2018)

The identification of data anomalies from information sensors based on the estimation of the correlation dimension of the time series attractor in situational management systems
di: Tebueva, F. B., et al.
Pubblicazione: (2018)