2013
DOI: 10.1016/j.physa.2013.07.011
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Stochastic resonance in hybrid scale-free neuronal networks

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Cited by 111 publications
(28 citation statements)
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“…It is precisely at this ‘optimal’ noise value at which SR increases the system’s sensitivity to detect information-carrying signals. SR is a phenomenon that also has been studied in models of single neurons (Bulsara et al, 1991; Wiesenfeld et al, 1994; Lee and Kim, 1999) and in models of small-world neural networks (Perc, 2007; Ozer et al, 2009; Wang et al, 2009; Yilmaz et al, 2013) due to the fact that it’s influenced by the network topology. The study of SR in neural networks could be of particular importance for the interpretation and discussion of psychophysical experiments involving the application of external noise.…”
Section: Introductionmentioning
confidence: 99%
“…It is precisely at this ‘optimal’ noise value at which SR increases the system’s sensitivity to detect information-carrying signals. SR is a phenomenon that also has been studied in models of single neurons (Bulsara et al, 1991; Wiesenfeld et al, 1994; Lee and Kim, 1999) and in models of small-world neural networks (Perc, 2007; Ozer et al, 2009; Wang et al, 2009; Yilmaz et al, 2013) due to the fact that it’s influenced by the network topology. The study of SR in neural networks could be of particular importance for the interpretation and discussion of psychophysical experiments involving the application of external noise.…”
Section: Introductionmentioning
confidence: 99%
“…the connections of communication system, terrorists' connections or the connections of landscape aesthetic values, can be analyzed paying special attention to the nature of scale-free networks and their features. Examples of random networks and scale-free networks are presented in Figure 1 The general characteristics of scale-free networks can be described in several points (Barabási and Bonabeau, 2003;Barabási, 2001;Hawoong , 1999, 2000;Cohen, 2002;Ercal and Matta, 2013;Li, Wang and Guan, 2014;Lou, S-L et al, 2013;Newman, Barabási and Watts, 2006;Yan, Ahmad and Yang, 2013;Yilmaz et al, 2013):…”
Section: Scale-free Networkmentioning
confidence: 99%
“…Particular, some authors argue that the probability for long-range connection in realistic network of neuron can be time-varying or changeable due to self-adaption. Surely, the scale-free network [28][29][30][31] is also effective to describe some statistical properties of the network. Generally, network can present several types of collective behaviors, order or disorder states, even transition from one mode to another mode by changing the bifurcation control parameters.…”
Section: Introductionmentioning
confidence: 99%