Influence of random topology in artificial neural networks: A survey

Sara Kaviani, Insoo Sohn

Research output: Contribution to journalReview articlepeer-review

18 Scopus citations

Abstract

Due to the fully-connected complex structure of Artificial Neural Networks (ANNs), systems based on ANN may consume much computational time, energy and space. Therefore, intense research has been recently centered on changing the topology and design of ANNs to obtain high performance. To explore the influence of network structure on ANNs complex systems topologies have been applied in these networks to have more efficient and less complex structures while they are more similar to biological systems at the same time. In this paper, the methodology and results of some recent papers are summarized and discussed in which the authors investigated the efficacy of random complex networks on the performance of Hopfield associative memory and multi-layer ANNs compared with ANNs with small-world, scale-free and regular structures.

Original languageEnglish
Pages (from-to)145-150
Number of pages6
JournalICT Express
Volume6
Issue number2
DOIs
StatePublished - Jun 2020

Keywords

  • Artificial neural networks
  • Complex systems
  • Random networks

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