Infocommunication systems parameter monitoring by means of artificial neural network devices

Danilin, S.N.; Makarov, Mikhail; Shchanikov, S.A.

doi:10.1109/crmico.2014.6959412

Cited by 4 publications

(2 citation statements)

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“…During this development the authors applied methods of designing ANNs with specified operation accuracy in the presence of real-time destabilizing factors described in [10][11][12]. The research results enabled the authors to propose a general approach to developing neural network algorithms for monitoring harmonic signal parameters.…”

Section: Methodsmentioning

confidence: 99%

“…In the works [8,9] the authors propose several neural network algorithms for assessing the parameters of harmonic signals based on the double-layer ANNs of feedforward type. During this development the authors applied methods of designing ANNs with specified operation accuracy in the presence of real-time destabilizing factors described in [10][11][12].…”

Section: Methodsmentioning

confidence: 99%

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Monitoring the phase progression of linear chirp by applying artificial neural networks

Danilin

Shchanikov

2016

2016 International Siberian Conference on Control and Communications (SIBCON)

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in this paper the authors propose a general approach to developing neural network algorithms aimed at monitoring of signal parameters and have developed a neural network algorithm designed to monitor the absolute value of a linear chirp (LFM) signal phase deviation. The authors show some possible ways of how to reduce an error probability of the neural algorithms when monitoring signal parameters in the technical check and control systems.

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Section: Methodsmentioning

confidence: 99%