Stochastic resonance for an optimal detector with phase noise

2003 ◽  
Vol 83 (3) ◽  
pp. 665-670 ◽  
Author(s):  
François Chapeau-Blondeau
2019 ◽  
Vol 88 (6) ◽  
pp. 063001 ◽  
Author(s):  
Jong-Hoon Huh ◽  
Yoshimitsu Yano ◽  
Naoto Miyagawa

2019 ◽  
Vol 33 (26) ◽  
pp. 1950302
Author(s):  
Xiao Li Yang ◽  
Xiao Qiang Liu

Through introducing the ingredients of electromagnetic induction and coupled time delay into the original Fitzhugh–Nagumo (FHN) neuronal network, the dynamics of stochastic resonance in a model of modified FHN neuronal network in the environment of phase noise is explored by numerical simulations in this study. On one hand, we demonstrate that the phenomenon of stochastic resonance can appear when the intensity of phase noise is appropriately adjusted, which is further verified to be robust to the edge-added probability of small-world network. Moreover, under the influence of electromagnetic induction, the phase noise-induced resonance response is suppressed, meanwhile, a large noise intensity is required to induce stochastic resonance as the feedback gain of induced current increases. On the other hand, when the coupled time delay is incorporated into this model, the results indicate that the properly tuned time delay can induce multiple stochastic resonances in this neuronal network. However, the phenomenon of multiple stochastic resonances is found to be restrained upon increasing feedback gain of induced current. Surprisingly, by changing the period of phase noise, multiple stochastic resonances can still emerge when the coupled time delay is appropriately tuned to be integer multiples of the period of phase noise.


2000 ◽  
Vol 61 (1) ◽  
pp. 940-943 ◽  
Author(s):  
François Chapeau-Blondeau

1990 ◽  
Vol 42 (11) ◽  
pp. 6651-6659 ◽  
Author(s):  
A. A. Rangwala ◽  
K. Wódkiewicz ◽  
C. Su

2018 ◽  
Author(s):  
Nicola Da Dalt ◽  
Ali Sheikholeslami
Keyword(s):  

2014 ◽  
Vol 2 ◽  
pp. 417-420
Author(s):  
Florian Gomez ◽  
Stefan Martignoli ◽  
Ruedi Stoop

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