Performance of networks of artificial neurons: The role of clustering

Details Performance of networks of artificial neurons: The role of clustering Performance of networks of artificial neurons: The role of clustering

2004-02-27

arxiv.org/abs/q-bio/0402045v1

Phys. Rev. E 69, 045101(R) (2004)

Biology

Quantitative Biology

Neurons and Cognition

4 pages, to appear in PRE as Rapid Comm

Scientific paper

10.1103/PhysRevE.69.045101

The performance of the Hopfield neural network model is numerically studied on various complex networks, such as the Watts-Strogatz network, the Barab{\'a}si-Albert network, and the neuronal network of the C. elegans. Through the use of a systematic way of controlling the clustering coefficient, with the degree of each neuron kept unchanged, we find that the networks with the lower clustering exhibit much better performance. The results are discussed in the practical viewpoint of application, and the biological implications are also suggested.

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