An Incremental Optimal Weight Learning Machine of Single-Layer Neural Networks
Joint Authors
Mei, Ying
Ke, Hai-Feng
Lu, Cheng-Bo
Li, Xiao-Bo
Zhang, Gao-Yan
Shen, Xue-Wen
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-03-01
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
An optimal weight learning machine with growth of hidden nodes and incremental learning (OWLM-GHNIL) is given by adding random hidden nodes to single hidden layer feedforward networks (SLFNs) one by one or group by group.
During the growth of the networks, input weights and output weights are updated incrementally, which can implement conventional optimal weight learning machine (OWLM) efficiently.
The simulation results and statistical tests also demonstrate that the OWLM-GHNIL has better generalization performance than other incremental type algorithms.
American Psychological Association (APA)
Ke, Hai-Feng& Lu, Cheng-Bo& Li, Xiao-Bo& Zhang, Gao-Yan& Mei, Ying& Shen, Xue-Wen. 2018. An Incremental Optimal Weight Learning Machine of Single-Layer Neural Networks. Scientific Programming،Vol. 2018, no. 2018, pp.1-7.
https://search.emarefa.net/detail/BIM-1214678
Modern Language Association (MLA)
Ke, Hai-Feng…[et al.]. An Incremental Optimal Weight Learning Machine of Single-Layer Neural Networks. Scientific Programming No. 2018 (2018), pp.1-7.
https://search.emarefa.net/detail/BIM-1214678
American Medical Association (AMA)
Ke, Hai-Feng& Lu, Cheng-Bo& Li, Xiao-Bo& Zhang, Gao-Yan& Mei, Ying& Shen, Xue-Wen. An Incremental Optimal Weight Learning Machine of Single-Layer Neural Networks. Scientific Programming. 2018. Vol. 2018, no. 2018, pp.1-7.
https://search.emarefa.net/detail/BIM-1214678
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1214678