Evolution of Modular Networks Under Selection for Non-Linearly Denoising
Yusuke Ikemoto* and Kosuke Sekiyama**
*Department of Mechanical Engineering, Meijo University
1-501 Shiogamaguchi, Tempaku, Nagoya, Japan
**Department of Micro-Nano Systems Engineering, Nagoya University
Furo-cho, Chikusa-ku, Nagoya, Japan
Many biological and artifact networks often represent modular structures in which the network can be decomposed into several subnetworks. Here, we propose a simple model for the modular network evolution based on the nonlinear denoising in node activities. This model suggests that modular networks can evolve under certain conditions — if the stipulated goals for the networks or the input and target output pairs involve modular features, or if the signal transfer in a node is carried out in a nonlinear manner with respect to the saturation at the upper and lower bounds. Our model highlights the positive role played by noise in modular network evolution.
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