DocumentCode
1797619
Title
Efficient diminished-1 modulo 2n+1 multiplier architectures
Author
Xiaolan Lv ; Ruohe Yao
Author_Institution
Sch. of Electron. & Inf. Eng., South China Univ. of Technol., Guangzhou, China
fYear
2014
fDate
6-11 July 2014
Firstpage
481
Lastpage
486
Abstract
The main components of an artificial neuron are adders and multipliers. In order to implement neural network, large number of adders and multipliers are required. The efficient architectures for diminished-1 modulo 2n+1 multipliers are described. The results and operands of the new modulo 2n+1 multipliers use the diminished-1, avoiding n+1 bit circuit. And the presented multipliers can handle zero inputs and results. The proposed modulo 2n +1 multiplier are built using three major functional modules, partial products generation block, partial products reduction block and a final diminished-1 adder block. The final modulo 2n +1 addition block is built around a sparse carry computation unit for the analytical and experimental results. And this indicates that the significant area and power of the proposed multipliers is superior to the earlier proposals, with a high operation speed.
Keywords
adders; multiplying circuits; neural nets; adders; artificial neuron; diminished-1 adder block; diminished-1 modulo 2n+1 multiplier architectures; functional modules; multipliers; neural network; operands; partial products generation block; partial products reduction block; sparse carry computation unit; Adders; Arrays; Biological neural networks; Delays; Logic gates; Vectors; Diminished-1 representation; Residue number system (RNS); VLSI; modular multiplier;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks (IJCNN), 2014 International Joint Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4799-6627-1
Type
conf
DOI
10.1109/IJCNN.2014.6889540
Filename
6889540
Link To Document