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Reseach Article

Low Power Adder based ANN

by S N Prasad, S.y. Kulkarni
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 118 - Number 10
Year of Publication: 2015
Authors: S N Prasad, S.y. Kulkarni
10.5120/20778-3335

S N Prasad, S.y. Kulkarni . Low Power Adder based ANN. International Journal of Computer Applications. 118, 10 ( May 2015), 1-4. DOI=10.5120/20778-3335

@article{ 10.5120/20778-3335,
author = { S N Prasad, S.y. Kulkarni },
title = { Low Power Adder based ANN },
journal = { International Journal of Computer Applications },
issue_date = { May 2015 },
volume = { 118 },
number = { 10 },
month = { May },
year = { 2015 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume118/number10/20778-3335/ },
doi = { 10.5120/20778-3335 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:01:17.018812+05:30
%A S N Prasad
%A S.y. Kulkarni
%T Low Power Adder based ANN
%J International Journal of Computer Applications
%@ 0975-8887
%V 118
%N 10
%P 1-4
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents an overview of datapath realizations of the Hardware neural network models which perform massive parallel operations for best results and real time applications. Digital implemented neural models processing element – adder with low power consumption is proposed for real-time multimedia applications. Proposed adder is illustrated in the 2-3-1 tree layer artificial neural network (ANN). Designs were modeled with Verilog HDL and implemented in FPGA domain by targeting the Virtex 7 device.

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Index Terms

Computer Science
Information Sciences

Keywords

ANN Low Power Adder Datapath Verilog HDL VLSI