DocumentCode
2030088
Title
A mixed signal multiplier using A2 binary representation dedicated to neural networks applications
Author
Boukadida, Hatem ; Hassen, Néjib ; Gafsi, Zied ; Besbes, Kamel
Author_Institution
Lab. de Microelectron. et Instrum. (μEi), Univ. Pierre et Marie Curie, Paris, France
fYear
2011
fDate
6-8 April 2011
Firstpage
1
Lastpage
4
Abstract
The main goal of our work is to investigate the delay performances of redundant binary arithmetic operators using different CMOS logic and mixed signals styles. This paper presents a novel technique for A2 redundant binary multiplication in mixed-signal circuits especially for neural networks applications. The proposed multiplier consists of three cascaded blocks: Two 3-bit Arithmetic Multiplier Digital to Analog Converter (AMDAC) cells, and one 6-bit Flash ADC. Our technique indicates that this approach significantly reduces the silicon area occupied by such multipliers compared to the classical scheme using combinational multipliers. The circuit being studied is optimized for speed efficiency at 0.35 μm CMOS process.
Keywords
CMOS logic circuits; mixed analogue-digital integrated circuits; neural nets; voltage multipliers; CMOS logic; arithmetic multiplier digital to analog converter cells; binary representation; mixed signal circuits; mixed signal multiplier; neural networks applications; redundant binary arithmetic operators; size 0.35 mum; Artificial neural networks; Biological neural networks; CMOS integrated circuits; Computers; Digital arithmetic; Neurons; System-on-a-chip; Computer arithmetic; Redundant binary representation; VLSI integration;
fLanguage
English
Publisher
ieee
Conference_Titel
Design & Technology of Integrated Systems in Nanoscale Era (DTIS), 2011 6th International Conference on
Conference_Location
Athens
Print_ISBN
978-1-61284-899-0
Type
conf
DOI
10.1109/DTIS.2011.5941407
Filename
5941407
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