Optimal signal amplification in weighted scale-free networks

Author(s)

Liang, Xiaoming ^{[1, 2, 3]} ; Zhao, Liang ^[3] ; Liu, Zonghua ^{[1, 2]}

Affiliation

^[1] E China Normal Univ, Inst Theoret Phys, Shanghai 200062 - Peoples R China

^[2] E China Normal Univ, Dept Phys, Shanghai 200062 - Peoples R China

^[3] Univ Fed Sao Carlos, Inst Math & Comp Sci, BR-13560970 Sao Carlos, SP - Brazil

• Document type: Journal article
• Source: Chaos; v. 22, n. 2 JUN 2012.
• Web of Science Citations: 5

Abstract

It has been revealed that un-weighted scale-free (SF) networks have an effect of amplifying weak signals {[}Acebron et al., Phys. Rev. Lett. 99, 128701 (2007)]. Such a property has potential applications in neural networks and artificial signaling devices. However, many real and artificial networks, including the neural networks, are weighted ones with adaptive and plastic couplings. For this reason, here we study how the weak signal can be amplified in weighted SF networks by introducing a parameter to self-tune the coupling weights. We find that the adaptive weights can significantly extend the range of coupling strength for signal amplification, in contrast to the relatively narrow range in un-weighted SF networks. As a consequence, the effect of finite network size occurred in un-weighted SF networks can be overcome. Finally, a theory is provided to confirm the numerical results. (C) 2012 American Institute of Physics. {[}http://dx.doi.org/10.1063/1.4718723] (AU)

• FAPESP's process: 11/03631-6 - Collective behavior of neurons in complex networks
• Grantee: Zhao Liang
• Support Opportunities: Research Grants - Visiting Researcher Grant - International
• FAPESP's process: 11/50151-0 - Dynamical phenomena in complex networks: fundamentals and applications
• Grantee: Elbert Einstein Nehrer Macau
• Support Opportunities: Research Projects - Thematic Grants