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Phase Coherence Induced by Additive Gaussian and Non-gaussian Noise in Excitable Networks With Application to Burst Suppression-Like Brain Signals [PDF]
Frontiers in Applied Mathematics and Statistics, 2020 It is well-known that additive noise affects the stability of non-linear systems. Using a network composed of two interacting populations, detailed stochastic and non-linear analysis demonstrates that increasing the intensity of iid additive noise ...
Axel Hutt +3 more
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An Improved Spectral Subtraction Method for Eliminating Additive Noise in Condition Monitoring System Using Fiber Bragg Grating Sensors [PDF]
SensorsThe additive noise in the condition monitoring system using fiber Bragg grating (FBG) sensors, including white Gaussian noise and multifrequency interference, has a significantly negative influence on the fault diagnosis of rotating machinery.
Qi Liu +3 more
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Skeleting of Low-Contrast Noisy Halftone Images
Доклады Белорусского государственного университета информатики и радиоэлектроники, 2023 The problem of forming the skeletons of halftone images with two-mode brightness histograms under conditions of changing contrast and noise is considered. On such histograms, one mode corresponds to the objects, and the other to the background. Thanks to
Ma Jun +2 more
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Bautin bifurcation with additive noise
Advances in Nonlinear Analysis, 2022 In this paper, we consider stochastic dynamics of a two-dimensional stochastic differential equation with additive noise. When the strength of the noise is zero, this equation undergoes a Bautin bifurcation.
Tang Diandian, Ren Jingli
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Remote Sensing, 2020 Quantifying information content in remote-sensing images is fundamental for information-theoretic characterization of remote sensing information processes, with the images being usually information sources.
Ying Zhang +2 more
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Analysis on Noisy Boltzmann Machines and Noisy Restricted Boltzmann Machines
IEEE Access, 2021 The Boltzmann machine (BM) and restricted Boltzmann machine (RBM) models are representative stochastic neural networks, in which neuron states are determined by stochastic activation functions. They are widely used in many applications.
Wenhao Lu, Chi-Sing Leung, John Sum
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IEEE Access, 2020 The traditional Cubature Kalman Filter (CKF) and its derived algorithms cannot work without the two hypotheses of Kalman Filter (KF), one is that the system model is accurate and the other is the system is only influenced by independent white noise with ...
J. Liu +6 more
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Open Mathematics, 2022 In this paper, the stochastic asymptotic behavior of the nonautonomous stochastic higher-order Kirchhoff equation with variable coefficients is studied.
Lv Penghui, Lin Guoguang, Sun Yuting
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Вестник Самарского университета: Естественнонаучная серия, 2023 For modeling in time series, models with fractional differences are widely used. The best known model is the ARFIMA (autoregressive fractionally integrated moving average) model.
Dmitriy V. Ivanov
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Overview of Identification Methods of Autoregressive Model in Presence of Additive Noise
Mathematics, 2023 This paper presents an overview of the main methods used to identify autoregressive models with additive noises. The classification of identification methods is given. For each group of methods, advantages and disadvantages are indicated.
Dmitriy Ivanov, Zaineb Yakoub
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