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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/50930

Title: On the internal representations of product unit
Contributors: 國立臺灣海洋大學:電機工程學系
Keywords: product unit
internal representations
recurrent neural networks
backpropagation training
Date: 2000-12
Issue Date: 2018-11-01T01:34:03Z
Publisher: Neural Processing Letters
Abstract: Abstract: This paper explores internal representation power of product units [1] that act as the
functional nodes in the hidden layer of a multi-layer feedforward network. Interesting properties
from using binary input provide an insight into the superior computational power of the product
unit. Using binary computation problems of symmetry and parity as illustrative examples, we
show that learning arbitrary complex internal representations is more achievable with product
units than with traditional summing units.
Relation: 12(3) pp.247-254
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/50930
Appears in Collections:[電機工程學系] 期刊論文

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