scholarly journals On the Breaking of the Milankovitch Cycles Triggered by Temperature Increase: The Stochastic Resonance Response

Climate ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 67
Author(s):  
Maria Teresa Caccamo ◽  
Salvatore Magazù
Keyword(s):  
Stochastic Resonance ◽  
Temperature Increase ◽  
Hot Spot ◽  
Climate Scenario ◽  
Threshold Effect ◽  
Chaotic Regime ◽  
Milankovitch Cycles ◽  
Intensity Increase ◽  
Resonance Model ◽  
Milankovitch Cycle

Recent decades have registered the hottest temperature variation in instrumentally recorded data history. The registered temperature rise is particularly significant in the so-called hot spot or sentinel regions, characterized by higher temperature increases in respect to the planet average value and by more marked connected effects. In this framework, in the present work, following the climate stochastic resonance model, the effects, due to a temperature increase independently from a specific trend, connected to the 105 year Milankovitch cycle were tested. As a result, a breaking scenario induced by global warming is forecasted. More specifically, a wavelet analysis, innovatively performed with different sampling times, allowed us, besides to fully characterize the cycles periodicities, to quantitatively determine the stochastic resonance conditions by optimizing the noise level. Starting from these system resonance conditions, numerical simulations for increasing planet temperatures have been performed. The obtained results show that an increase of the Earth temperature boosts a transition towards a chaotic regime where the Milankovitch cycle effects disappear. These results put into evidence the so-called threshold effect, namely the fact that also a small temperature increase can give rise to great effects above a given threshold, furnish a perspective point of view of a possible future climate scenario, and provide an account of the ongoing registered intensity increase of extreme meteorological events.

scholarly journals A Physical–Mathematical Approach to Climate Change Effects through Stochastic Resonance

Climate ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 21 ◽  
Author(s):  
Maria Caccamo ◽  
Salvatore Magazù
Keyword(s):  
Stochastic Resonance ◽  
Temperature Increase ◽  
Global Temperature ◽  
Effect Of Temperature ◽  
Periodic Modulation ◽  
Glacial Cycles ◽  
Resonance Model ◽  
Cross Correlation Analysis ◽  
The Impact ◽  
Earth Temperature

The aim of this work is to study the effects induced by climate changes in the framework of the stochastic resonance approach. First, a wavelet cross-correlation analysis on Earth temperature data concerning the last 5,500,000 years is performed; this analysis confirms a correlation between the planet’s temperature and the 100,000, 41,000, and 23,000-year periods of the Milankovitch orbital cycles. Then, the stochastic resonance model is invoked. Specific attention is given to the study of the impact of the registered global temperature increase within the stochastic model. Further, a numerical simulation has been performed, based on: (1) A double-well potential, (2) an external periodic modulation, corresponding to the orbit eccentricity cycle, and (3) an increased value of the global Earth temperature. The effect of temperature increase represents one of the novelties introduced in the present study and is determined by downshifting the interaction potential used within the stochastic resonance model. The numeric simulation results show that, for simulated increasing values of the global temperature, the double-well system triggers changes, while at higher temperatures (as in the case of the absence of a global temperature increase although with a different threshold) the system goes into a chaotic regime. The wavelet analysis allows characterization of the stochastic resonance condition through the evaluation of the signal-to-noise ratio. On the basis of the obtained findings, we hypothesize that the global temperature increase can suppress, on a large time scale corresponding to glacial cycles, the external periodic modulation effects and, hence, the glacial cycles.

A novel stochastic resonance model based on bistable stochastic pooling network and its application

2021 ◽  
Vol 145 ◽  
pp. 110800
Author(s):  
Wenyue Zhang ◽  
Peiming Shi ◽  
Mengdi Li ◽  
Dongying Han
Keyword(s):  
Stochastic Resonance ◽  
Resonance Model ◽  
Model Based ◽  
Stochastic Pooling

Orbital forcing in a stochastic resonance model of the Late-Pleistocene climatic variations

1989 ◽  
Vol 3 (4) ◽  
pp. 179-190 ◽  
Author(s):  
Gianni Matteucci
Keyword(s):  
Stochastic Resonance ◽  
Late Pleistocene ◽  
Orbital Forcing ◽  
Resonance Model ◽  
Climatic Variations

scholarly journals Actuator Weak Fault Diagnosis in Autonomous Underwater Vehicle Based on Tri-Stable Stochastic Resonance

2020 ◽  
Vol 10 (6) ◽  
pp. 2048 ◽  
Author(s):  
Yang Jiang ◽  
Bo He ◽  
Jia Guo ◽  
Pengfei Lv ◽  
Xiaokai Mu ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Stochastic Resonance ◽  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Ant Colony ◽  
Resonance System ◽  
Resonance Model ◽  
Weak Fault

The autonomous underwater vehicle (AUV) is mainly used in the development and exploration of the ocean. As an important module of the AUV, the actuator plays an important role in the normal execution of the AUV. Therefore, the fault diagnosis of the actuator is particularly important. At present, the research on the strong faults, such as the winding of the actuator, has achieved good results, but the research on the weak fault diagnosis is relatively rare. In this paper, the tri-stable stochastic resonance model is analyzed, and the ant colony tri-stable stochastic resonance model is used to diagnose the weak fault. The system accurately diagnoses the fault of the actuator collision and verifies the adaptive tri-stable stochastic resonance system. This model has better diagnostic results than the bi-stable stochastic resonance system.

scholarly journals Stochastic resonance model of synaesthesia

2019 ◽  
Vol 374 (1787) ◽  
pp. 20190029 ◽  
Author(s):  
Poortata Lalwani ◽  
David Brang
Keyword(s):  
Stochastic Resonance ◽  
Cortical Excitability ◽  
Sensory Modality ◽  
Unified Framework ◽  
Resonance Model ◽  
Neural Noise ◽  
Sensory Experiences ◽  
Perceptual Differences ◽  
Broader Phenotype ◽  
Novel Model

In synaesthesia, stimulation of one sensory modality evokes additional experiences in another modality (e.g. sounds evoking colours). Along with these cross-sensory experiences, there are several cognitive and perceptual differences between synaesthetes and non-synaesthetes. For example, synaesthetes demonstrate enhanced imagery, increased cortical excitability and greater perceptual sensitivity in the concurrent modality. Previous models suggest that synaesthesia results from increased connectivity between corresponding sensory regions or disinhibited feedback from higher cortical areas. While these models explain how one sense can evoke qualitative experiences in another, they fail to predict the broader phenotype of differences observed in synaesthetes. Here, we propose a novel model of synaesthesia based on the principles of stochastic resonance. Specifically, we hypothesize that synaesthetes have greater neural noise in sensory regions, which allows pre-existing multisensory pathways to elicit supra-threshold activation (i.e. synaesthetic experiences). The strengths of this model are (a) it predicts the broader cognitive and perceptual differences in synaesthetes, (b) it provides a unified framework linking developmental and induced synaesthesias, and (c) it explains why synaesthetic associations are inconsistent at onset but stabilize over time. We review research consistent with this model and propose future studies to test its limits. This article is part of a discussion meeting issue ‘Bridging senses: novel insights from synaesthesia’.

scholarly journals The Enhancement of Weak Bearing Fault Signatures by Stochastic Resonance with a Novel Potential Function

Energies ◽  
2020 ◽  
Vol 13 (23) ◽  
pp. 6348
Author(s):  
Chao Zhang ◽  
Haoran Duan ◽  
Yu Xue ◽  
Biao Zhang ◽  
Bin Fan ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Stochastic Resonance ◽  
Operating Conditions ◽  
Detection Accuracy ◽  
Wind Turbine Gearbox ◽  
Resonance Model ◽  
Function Type ◽  
Vibration Signals ◽  
Fourier Decomposition ◽  
Bearing Fault

As the critical parts of wind turbines, rolling bearings are prone to faults due to the extreme operating conditions. To avoid the influence of the faults on wind turbine performance and asset damages, many methods have been developed to monitor the health of bearings by accurately analyzing their vibration signals. Stochastic resonance (SR)-based signal enhancement is one of effective methods to extract the characteristic frequencies of weak fault signals. This paper constructs a new SR model, which is established based on the joint properties of both Power Function Type Single-Well and Woods-Saxon (PWS), and used to make fault frequency easy to detect. However, the collected vibration signals usually contain strong noise interference, which leads to poor effect when using the SR analysis method alone. Therefore, this paper combines the Fourier Decomposition Method (FDM) and SR to improve the detection accuracy of bearing fault signals feature. Here, the FDM is an alternative method of empirical mode decomposition (EMD), which is widely used in nonlinear signal analysis to eliminate the interference of low-frequency coupled signals. In this paper, a new stochastic resonance model (PWS) is constructed and combined with FDM to enhance the vibration signals of the input and output shaft of the wind turbine gearbox bearing, make the bearing fault signals can be easily detected. The results show that the combination of the two methods can detect the frequency of a bearing failure, thereby reminding maintenance personnel to urgently develop a maintenance plan.

Experimental study of stochastic resonance in a Chua’s circuit operating in a chaotic regime

2006 ◽  
Vol 219 (1) ◽  
pp. 93-100 ◽  
Author(s):  
Wojciech Korneta ◽  
Iacyel Gomes ◽  
Claudio R. Mirasso ◽  
Raúl Toral
Keyword(s):  
Experimental Study ◽  
Stochastic Resonance ◽  
Chaotic Regime ◽  
Chua’S Circuit ◽  
Chua's Circuit

scholarly journals Topic Relevance of Public Health Emergencies Influence on Internet Public Opinion Resonance: Simulation Based on Langevin’s Equation

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Quan Cheng ◽  
Yan-gang Zhang ◽  
Yi-quan Li
Keyword(s):  
Public Health ◽  
Public Opinion ◽  
Stochastic Resonance ◽  
Resonance Phenomenon ◽  
The Internet ◽  
Resonance Model ◽  
Mutual Correlation ◽  
The Public ◽  
Public Health Emergencies ◽  
Topic Relevance

Public health emergencies occurred frequently, which usually result in the negative Internet public opinion events. In the complex network information ecological environment, multiple public opinion events may be aggregated to generate public opinion resonance due to the topic category, the mutual correlation of the subject involved, and the compound accumulation of specific emotions. In order to reveal the phenomenon and regulations of the public opinion resonance, we firstly analyze the influence factors of the Internet public opinion events in the public health emergencies. Then, based on Langevin’s equation, we propose the Internet public opinion stochastic resonance model considering the topic relevance. Furthermore, three exact public health emergencies in China are provided to reveal the regulations of evoked events “revival” caused by original events. We observe that the Langevin stochastic resonance model considering topic relevance can effectively reveal the resonance phenomenon of Internet public opinion caused by public health emergencies. For the original model without considering the topic relevance, the new model is more sensitive. Meanwhile, it is found that the degree of topic relevance between public health emergencies has a significant positive correlation with the intensity of Internet public opinion resonance.

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