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Publications in Math-Net.Ru
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Studying electrical activity of the brain within the concept of coordination of rhythmic processes
Izvestiya VUZ. Applied Nonlinear Dynamics, 32:4 (2024), 511–520
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Extended method of cross-correlation analysis of non-stationary processes
Pisma v Zhurnal Tekhnicheskoi Fiziki, 50:10 (2024), 40–42
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Application of joint singularity spectrum to analyze cooperative dynamics of complex systems
Izvestiya VUZ. Applied Nonlinear Dynamics, 31:3 (2023), 305–315
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Analysis of the cooperative dynamics of nonlinear systems based on joint singularity spectrum
Pisma v Zhurnal Tekhnicheskoi Fiziki, 49:10 (2023), 6–8
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Diagnostics of changes in the dynamics of complex systems from transient processes based on multiresolution wavelet analysis
Pisma v Zhurnal Tekhnicheskoi Fiziki, 49:2 (2023), 7–9
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Fluctuation analysis of the dynamics of systems with time-varying characteristics
Pisma v Zhurnal Tekhnicheskoi Fiziki, 47:9 (2021), 52–54
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Multiscale analysis of rhythmic processes with time-varying characteristics
Pisma v Zhurnal Tekhnicheskoi Fiziki, 46:18 (2020), 7–9
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A modified fluctuation analysis of nonstationary processes
Pisma v Zhurnal Tekhnicheskoi Fiziki, 46:6 (2020), 47–50
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The influence of switching between chaotic regimes on the correlation characteristics of nonlinear systems
Pisma v Zhurnal Tekhnicheskoi Fiziki, 45:18 (2019), 6–8
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Use of wavelets for recognizing types of motion by means of data on the electrical activity of the brain
Pisma v Zhurnal Tekhnicheskoi Fiziki, 45:16 (2019), 24–26
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Recognizing arm motions by fluctuation analysis of EEG signals
Pisma v Zhurnal Tekhnicheskoi Fiziki, 45:4 (2019), 8–10
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A method for increasing the accuracy in calculating the characteristics of complex dynamics of threshold systems
Pisma v Zhurnal Tekhnicheskoi Fiziki, 44:15 (2018), 65–70
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The influence of data loss on diagnostics of complex system dynamics
Pisma v Zhurnal Tekhnicheskoi Fiziki, 44:14 (2018), 80–85
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Computing spectral characteristics from short signals and nonstationary processes
Pisma v Zhurnal Tekhnicheskoi Fiziki, 44:2 (2018), 3–10
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Analysis of chaotic dynamic regimes using series of interburst intervals
Zhurnal Tekhnicheskoi Fiziki, 87:11 (2017), 1753–1755
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Noisy signal filtration using complex wavelet basis sets
Pisma v Zhurnal Tekhnicheskoi Fiziki, 43:14 (2017), 10–18
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Estimating the predictability time of noisy chaotic dynamics from point sequences
Pisma v Zhurnal Tekhnicheskoi Fiziki, 43:2 (2017), 45–51
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Speech signal filtration using double-density dual-tree complex wavelet transform
Pisma v Zhurnal Tekhnicheskoi Fiziki, 42:16 (2016), 72–78
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Wavelet filtration of noisy images
Pisma v Zhurnal Tekhnicheskoi Fiziki, 42:2 (2016), 50–56
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Largest Lyapunov exponent of chaotic oscillatory regimes computing from point processes in the noise presence
Izvestiya VUZ. Applied Nonlinear Dynamics, 23:6 (2015), 31–39
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Noise-induced loss of multifractality in dynamics of systems with self-sustained oscillations
Pisma v Zhurnal Tekhnicheskoi Fiziki, 41:22 (2015), 89–94
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Errors of analysis of parameters of complex oscillation regimes using point sequences of the integrate-and-fire model
Pisma v Zhurnal Tekhnicheskoi Fiziki, 41:21 (2015), 74–79
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Control for statistical characteristics of chaotic oscillation regimes by noise exposure
Pisma v Zhurnal Tekhnicheskoi Fiziki, 41:15 (2015), 105–110
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Digital audio signal filtration based on the dual-tree wavelet transform
Pisma v Zhurnal Tekhnicheskoi Fiziki, 41:14 (2015), 33–38
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Diagnostics of the regime of hyperchaotic dynamics from sequences of threshold-crossing time intervals
Pisma v Zhurnal Tekhnicheskoi Fiziki, 41:6 (2015), 98–104
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Adaptive wavelet analysis of optical coherent tomography data: Application in problems of diagnostics
Pisma v Zhurnal Tekhnicheskoi Fiziki, 39:19 (2013), 86–94
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A method for protecting communicated information using neural-network detection
Pisma v Zhurnal Tekhnicheskoi Fiziki, 39:18 (2013), 61–69
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Wavelet analysis in neurodynamics
UFN, 182:9 (2012), 905–939
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Synchronous dynamics of nephrons ensembles
Izv. Sarat. Univ. Physics, 11:1 (2011), 3–10
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Identification of action potentials of small neuron ensembles using wavelet-analysis and neural networks method
Izv. Sarat. Univ. Physics, 9:2 (2009), 57–65
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Multifractal analysis of signals based on wavelet-transform
Izv. Sarat. Univ. Physics, 7:1 (2007), 3–25
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Multifractal analysis of complex signals
UFN, 177:8 (2007), 859–876
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