Application of Neuroet Network Technology for Flikker-Noise Spectroscopy of Electrocardiogram

Abdullaev, N. T.; Qasankuliyeva, М. М.; Dzhabieva, A. Dj.; Republic, Industry, Baku city, az , Azerbaijan

doi:10.17587/it.24.402-405

Cited by 2 publications

(1 citation statement)

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“…As a result of analyzing the power spectrum S(f), informative parameters were obtained for the singular component of the ECG signal: T 0 , determining some characteristic time within which the measured dynamic variable is interconnected Vt i ðÞ ; n 0 , dimensionless parameter that effectively determines how this relationship is lost as frequencies decrease to 1=2πT 0 ; and s 0 ðÞ , contribution to the power spectrum S(f), determined by the most high-frequency singular component [5].…”

Section: The Use Of Neural Network Technology In Flicker-noise Spectrmentioning

confidence: 99%

Flicker-Noise Spectroscopy Method in the Problem of Diagnosing the State of the Cardiovascular System

Tahir¹,

Ramiz²

2021

Data Acquisition - Recent Advances and Applications in Biomedical Engineering

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In the field of research of the cardiovascular system, mainly analysis methods that are strictly mathematically applicable to stationary signals are distinguished; however, nonstationary signals prevail in medical practice, the statistical properties of which vary with time. Often they consist of short-term high-frequency components, followed by long-term low-frequency components. Given this nature of bioelectric potentials, and in particular electrocardiographic signals, the most suitable for their analysis may be the nonlinear dynamics method with the calculation of quantitative characteristics of chaos. This possibility is presented by the flickernoise spectroscopy method, which takes into account the intermittency effect in a complex dynamic system when sections of chaotic bursts and jumps alternate with relatively long sections of a laminar nature. The analysis of signals of such a dynamic nature is usually based on the use of flicker-noise spectroscopy.

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Section: The Use Of Neural Network Technology In Flicker-noise Spectrmentioning

confidence: 99%

Flicker-Noise Spectroscopy Method in the Problem of Diagnosing the State of the Cardiovascular System

Tahir¹,

Ramiz²

2021

Data Acquisition - Recent Advances and Applications in Biomedical Engineering

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Independent Assessment of the Implementation of the 2020 State Budget of Azerbaijan

Islamli¹

2021

SSRN Journal

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Application of Neuroet Network Technology for Flikker-Noise Spectroscopy of Electrocardiogram

Cited by 2 publications

References 0 publications

Flicker-Noise Spectroscopy Method in the Problem of Diagnosing the State of the Cardiovascular System

Flicker-Noise Spectroscopy Method in the Problem of Diagnosing the State of the Cardiovascular System

Independent Assessment of the Implementation of the 2020 State Budget of Azerbaijan

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