Influence of random topology in artificial neural networks: A survey

被引：8

作者：

Kaviani, Sara ^{[1
]}

Sohn, Insoo ^{[1
]}

机构：

[1] Dongguk Univ, Div Elect & Elect Engn, Seoul, South Korea

来源：

ICT EXPRESS | 2020年 / 6卷 / 02期

基金：

新加坡国家研究基金会;

关键词：

Complex systems; Artificial neural networks; Random networks; MEMORY; PERFORMANCE; MODEL;

D O I：

10.1016/j.icte.2020.01.002

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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. (C) 2020 The Korean Institute of Communications and Information Sciences (KICS). Publishing services by Elsevier B.V.

引用

页码：145 / 150

页数：6

共 36 条

[11] A neural network model of chemotaxis predicts functions of synaptic connections in the nematode Caenorhabditis elegans
Dunn, NA
Lockery, SR
Pierce-Shimomura, JT
Conery, JS
[J]. JOURNAL OF COMPUTATIONAL NEUROSCIENCE, 2004, 17 (02) : 137 - 147
[12] Performance of small-world feedforward neural networks for the diagnosis of diabetes
Erkaymaz, Okan
Ozer, Mahmut
Perc, Matja
[J]. APPLIED MATHEMATICS AND COMPUTATION, 2017, 311 : 22 - 28
[13] Gros Claudius., 2010, COMPLEX ADAPTIVE DYN, DOI 10.1007/978-3-642-04706-0
[14] Licensed-Assisted Access for LTE in Unlicensed Spectrum: A MAC Protocol Design
Han, Shiying
Liang, Ying-Chang
Chen, Qian
Soong, Boon-Hee
[J]. 2016 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), 2016,
[15] Hertz J., 1991, Phys Today, V44, P70, DOI [10.1063/1.2810360, DOI 10.1063/1.2810360]
[16] Statistical connectivity provides a sufficient foundation for specific functional connectivity in neocortical neural microcircuits
Hill, Sean L.
Wang, Yun
Riachi, Imad
Schuermann, Felix
Markram, Henry
[J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2012, 109 (42) : E2885 - E2894
[17] NEURAL NETWORKS AND PHYSICAL SYSTEMS WITH EMERGENT COLLECTIVE COMPUTATIONAL ABILITIES
HOPFIELD, JJ
[J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA-BIOLOGICAL SCIENCES, 1982, 79 (08): : 2554 - 2558
[18] ASSOCIATIVE RECALL OF MEMORY WITHOUT ERRORS
KANTER, I
SOMPOLINSKY, H
[J]. PHYSICAL REVIEW A, 1987, 35 (01): : 380 - 392
[19] How high is the level of technical noise in microarray data?
Klebanov, Lev
Yakovlev, Andrei
[J]. BIOLOGY DIRECT, 2007, 2 (1)
[20] Kovalenko I. N., 1971, Cybernetics, V7, P575, DOI 10.1007/BF01071028

← 1 2 3 4 →