A regeneratable dynamic differential evolution algorithm for neural networks with integer weights
A regeneratable dynamic differential evolution algorithm for neural networks with integer weights
About this item
Full title
Author / Creator
Bao, Jian , Chen, Yu and Yu, Jin-shou
Publisher
Heidelberg: Springer Nature B.V
Journal title
Language
English
Formats
Publication information
Publisher
Heidelberg: Springer Nature B.V
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Scope and Contents
Contents
Neural networks with integer weights are more suited for embedded systems and hardware implementations than those with real weights. However, many learning algorithms, which have been proposed for training neural networks with float weights, are inefficient and difficult to train for neural networks with integer weights. In this paper, a novel rege...
Alternative Titles
Full title
A regeneratable dynamic differential evolution algorithm for neural networks with integer weights
Authors, Artists and Contributors
Author / Creator
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Primary Identifiers
Record Identifier
TN_cdi_proquest_journals_2918723182
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2918723182
Other Identifiers
ISSN
2095-9184
E-ISSN
2095-9230
DOI
10.1631/jzus.C1000137
