Global stability and positive recurrence of a stochastic SIS model with Lévy noise perturbation

2019 ◽  
Vol 523 ◽  
pp. 677-690 ◽  
Author(s):  
Tomás Caraballo ◽  
Adel Settati ◽  
Mohamed El Fatini ◽  
Aadil Lahrouz ◽  
Abdelouahid Imlahi
Keyword(s):  
Global Stability ◽  
Lévy Noise ◽  
Sis Model ◽  
Positive Recurrence ◽  
Noise Perturbation ◽  
Levy Noise ◽  
Stochastic Sis Model

Media effects on the dynamics of a stochastic SIRI epidemic model with relapse and Lévy noise perturbation

2019 ◽  
Vol 12 (03) ◽  
pp. 1950037 ◽  
Author(s):  
Badr-Eddine Berrhazi ◽  
Mohamed El Fatini ◽  
Roger Pettersson ◽  
Aziz Laaribi
Keyword(s):  
Epidemic Model ◽  
Media Coverage ◽  
Deterministic Model ◽  
Dynamic Properties ◽  
Lévy Noise ◽  
Noise Perturbation ◽  
Global Positive Solution ◽  
Levy Noise ◽  
Theoretical Results ◽  
Disease Free

In this paper, we study the dynamic properties of an SIRI epidemic model incorporating media coverage, and stochastically perturbed by a Lévy noise. We establish the existence of a unique global positive solution. We investigate the dynamic properties of the solution around both disease-free and endemic equilibria points of the deterministic model depending on the basic reproduction number under some noise excitation. Furthermore, we present some numerical simulations to support the theoretical results.

Lévy noise perturbation for an epidemic model with impact of media coverage

Stochastics ◽  
2019 ◽  
Vol 91 (7) ◽  
pp. 998-1019 ◽  
Author(s):  
Mohamed El Fatini ◽  
Aziz Laaribi ◽  
Roger Pettersson ◽  
Regragui Taki
Keyword(s):  
Epidemic Model ◽  
Media Coverage ◽  
Lévy Noise ◽  
Noise Perturbation ◽  
Levy Noise

Stochastic resonance with multiplicative heavy-tailed Lévy noise: Optimal tuning on an algebraic time scale

2017 ◽  
Vol 17 (04) ◽  
pp. 1750027 ◽  
Author(s):  
Isabelle Kuhwald ◽  
Ilya Pavlyukevich
Keyword(s):  
Stochastic Resonance ◽  
Heavy Tails ◽  
Bistable System ◽  
Lévy Noise ◽  
Small Noise ◽  
Optimal Tuning ◽  
Noise Perturbation ◽  
Heavy Tailed ◽  
Synchronization Effect ◽  
Levy Noise

Stochastic resonance is an amplification and synchronization effect of weak periodic signals in nonlinear systems through a small noise perturbation. In this paper we study the dynamics of stochastic resonance in a bistable system driven by multiplicative Lévy noise with heavy tails, e.g., [Formula: see text]-stable Lévy noise. We determine the optimal tuning with respect to a probabilistic synchronization measure for both the jump-diffusion and the reduced two-state Markov chain. These results extend the theory of stochastic resonance to the case of heavy tail Lévy perturbations.

scholarly journals An Enhanced Intrinsic Time-Scale Decomposition Method Based on Adaptive Lévy Noise and Its Application in Bearing Fault Diagnosis

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 617
Author(s):  
Jianpeng Ma ◽  
Shi Zhuo ◽  
Chengwei Li ◽  
Liwei Zhan ◽  
Guangzhu Zhang
Keyword(s):  
Fault Diagnosis ◽  
Time Scale ◽  
Lévy Noise ◽  
Model Parameters ◽  
Rolling Bearings ◽  
Intrinsic Time ◽  
Time Scale Decomposition ◽  
Weak Fault ◽  
Levy Noise ◽  
The Impact

When early failures in rolling bearings occur, we need to be able to extract weak fault characteristic frequencies under the influence of strong noise and then perform fault diagnosis. Therefore, a new method is proposed: complete ensemble intrinsic time-scale decomposition with adaptive Lévy noise (CEITDALN). This method solves the problem of the traditional complete ensemble intrinsic time-scale decomposition with adaptive noise (CEITDAN) method not being able to filter nonwhite noise in measured vibration signal noise. Therefore, in the method proposed in this paper, a noise model in the form of parameter-adjusted noise is used to replace traditional white noise. We used an optimization algorithm to adaptively adjust the model parameters, reducing the impact of nonwhite noise on the feature frequency extraction. The experimental results for the simulation and vibration signals of rolling bearings showed that the CEITDALN method could extract weak fault features more effectively than traditional methods.

scholarly journals A Stochastic Kinetic Type Reactions Model for COVID-19

Mathematics ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1221
Author(s):  
Giorgio Sonnino ◽  
Fernando Mora ◽  
Pasquale Nardone
Keyword(s):  
Real Data ◽  
Stochastic Noise ◽  
Mathematical Basis ◽  
Sis Model ◽  
Theoretical Predictions ◽  
Coronavirus Infection ◽  
Massive Distribution ◽  
Second Wave ◽  
Stochastic Sis Model

We propose two stochastic models for the Coronavirus pandemic. The statistical properties of the models, in particular the correlation functions and the probability density functions, were duly computed. Our models take into account the adoption of lockdown measures as well as the crucial role of hospitals and health care institutes. To accomplish this work we adopt a kinetic-type reaction approach where the modelling of the lockdown measures is obtained by introducing a new mathematical basis and the intensity of the stochastic noise is derived by statistical mechanics. We analysed two scenarios: the stochastic SIS-model (Susceptible ⇒ Infectious ⇒ Susceptible) and the stochastic SIS-model integrated with the action of the hospitals; both models take into account the lockdown measures. We show that, for the case of the stochastic SIS-model, once the lockdown measures are removed, the Coronavirus infection will start growing again. However, the combined contributions of lockdown measures with the action of hospitals and health institutes is able to contain and even to dampen the spread of the SARS-CoV-2 epidemic. This result may be used during a period of time when the massive distribution of vaccines in a given population is not yet feasible. We analysed data for USA and France. In the case of USA, we analysed the following situations: USA is subjected to the first wave of infection by Coronavirus and USA is in the second wave of SARS-CoV-2 infection. The agreement between theoretical predictions and real data confirms the validity of our approach.

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