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INTEGER-WEIGHT NEURAL NETS
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UNSPECIFIED (1994) INTEGER-WEIGHT NEURAL NETS. ELECTRONICS LETTERS, 30 (15). pp. 1237-1238. ISSN 0013-5194.
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Abstract
Integer-weight neural nets (IWNN) are better suited for hardware implementation than their real-weight analogues. The authors present a learning procedure for generating multilayer IWNNs having all weights in the set {-3, -2, -1, 0, 1, 2, 3}. The performance of this procedure was evaluated on XOR, encoder/decoder and the MONK benchmark. The IWNNs were found to be as capable as their real-weight counterparts with regard to generalisation performance.
Item Type: | Journal Article | ||||
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Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering | ||||
Journal or Publication Title: | ELECTRONICS LETTERS | ||||
Publisher: | IEE-INST ELEC ENG | ||||
ISSN: | 0013-5194 | ||||
Official Date: | 21 July 1994 | ||||
Dates: |
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Volume: | 30 | ||||
Number: | 15 | ||||
Number of Pages: | 2 | ||||
Page Range: | pp. 1237-1238 | ||||
Publication Status: | Published |
Data sourced from Thomson Reuters' Web of Knowledge
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