scholarly journals System size stochastic resonance in asymmetric bistable coupled network systems

2014 ◽  
Vol 63 (22) ◽  
pp. 220503
Author(s):  
Sun Zhong-Kui ◽  
Lu Peng-Ju ◽  
Xu Wei
Keyword(s):  
Stochastic Resonance ◽  
System Size ◽  
Network Systems

System size stochastic resonance in driven finite arrays of coupled bistable elements

2010 ◽  
Vol 74 (2) ◽  
pp. 211-215 ◽  
Author(s):  
M. Morillo ◽  
J. Gómez-Ordóñez ◽  
J. M. Casado
Keyword(s):  
Stochastic Resonance ◽  
System Size

scholarly journals INTERPLAY BETWEEN CHAOS AND EXTERNAL NOISE IN AN EXTENDED SYSTEM: IMPROVED FORECASTING DUE TO INTRINSIC STOCHASTIC RESONANT PHENOMENA

2010 ◽  
Vol 20 (02) ◽  
pp. 213-224 ◽  
Author(s):  
JORGE A. REVELLI ◽  
MIGUEL A. RODRIGUEZ ◽  
HORACIO S. WIO
Keyword(s):  
Stochastic Resonance ◽  
System Size ◽  
External Noise ◽  
Resonance Phenomenon ◽  
Periodic Signal ◽  
Extended System ◽  
Underlying Mechanisms ◽  
Lorenz 96 ◽  
Stochastic Resonance Phenomenon ◽  
Resonant Phenomena

We have investigated the effects of noise on an extended chaotic system using as benchmark the Lorenz'96 model. The analysis of the system's time evolution and its time and space correlations show numerical evidence for two distinct stochastic resonance-like behaviors as a function of the external noise intensity, or the system size, and they result to be only weakly sensitive to an external periodic signal. The underlying mechanisms can be associated to a noise induced chaos reduction. A new view of the stochastic resonance phenomenon in a nonstationary situation is shown, studying the resonant phenomena implications in forecasting by exploiting a new method that quantifies the reduction of chaos error evolution process.

Review on Fog Based Spectrum Sensing for Artificial Intelligence

2018 ◽  
pp. 66-70
Author(s):  
A. Rethina Palin ◽  
I. Jeena Jacob
Keyword(s):  
Bandwidth Allocation ◽  
Situational Awareness ◽  
Cluster Head ◽  
Mesh Network ◽  
Network Systems ◽  
Markov Logic ◽  
Wireless Mesh ◽  
Local Environments ◽  
Reactive Routing ◽  
The Hierarchical Structure

Wireless Mesh Network (MWN) could be divided into proactive routing, reactive routing and hybrid routing, which must satisfy the requirements related to scalability, reliability, flexibility, throughput, load balancing, congestion control and efficiency. DMN (Directional Mesh Network) become more adaptive to the local environments and robust to spectrum changes. The existing computing units in the mesh network systems are Fog nodes, the DMN architecture is more economic and efficient since it doesn’t require architecture- level changes from existing systems. The cluster head (CH) manages a group of nodes such that the network has the hierarchical structure for the channel access, routing and bandwidth allocation. The feature extraction and situational awareness is conducted, each Fog node sends the information regarding the current situation to the cluster head in the contextual format. A Markov logic network (MLN) based reasoning engine is utilized for the final routing table updating regarding the system uncertainty and complexity.

Stochastic resonance in the peripheral auditory system

2014 ◽  
Vol 2 ◽  
pp. 417-420
Author(s):  
Florian Gomez ◽  
Stefan Martignoli ◽  
Ruedi Stoop
Keyword(s):  
Stochastic Resonance ◽  
Auditory System ◽  
Peripheral Auditory System

Information Aggregation via Stochastic Resonance in Moments

2014 ◽  
Vol 1 ◽  
pp. 13-16
Author(s):  
Akihisa Ichiki ◽  
Yukihiro Tadokoro
Keyword(s):  
Stochastic Resonance ◽  
Information Aggregation

Hybrid Vibration Energy Harvester based on Stochastic Resonance

2018 ◽  
Vol 138 (5) ◽  
pp. 185-190
Author(s):  
Meng Su ◽  
Dai Kobayashi ◽  
Nobuyuki Takama ◽  
Beomjoon Kim
Keyword(s):  
Stochastic Resonance ◽  
Energy Harvester ◽  
Vibration Energy ◽  
Vibration Energy Harvester
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