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110510

EFFICIENT HARDWARE IMPLEMENATATIONS OF FEEDFORWARD NEURAL NETWORKS USING FIELD PROGRAMMABLE GATE ARRAY

Article

Last updated: 26 Dec 2024

OverviewSimilar Items

Subjects

-

Tags

Electrical Engineering, Computer Engineering and Electrical power and machines engineering.

Abstract

Hardware implementation of Artificial Neural Network (ANNs) depends mainly on the efficient implementation of the activation functions. Field Programmable Gate Array is the most appropriate tool for hardware implementation of ANNs. In this paper we introduce FPGA-based hardware implementation of ANNs using five different activation functions. These implemented NNs are described using Very High Speed Integrated Circuits Hardware Description Language (VHDL) and carried out by Digilent Basys 2 Spartan-3E FPGA platform from Xilinx. The performances of the implemented NNs were investigated in terms of area efficient implementation, and correct prediction percentages for solving XOR, and Full-Adder problems.

DOI

10.21608/jesaun.2018.110510

Keywords

Artificial system, VHDL, FFNN, FPGA, Back-propagation, Activation function

Authors

First Name

Mohamed H.

Last Name

Essai

MiddleName

-

Affiliation

Electrical Eng. Depart, Faculty of Engineering-Qena, Al-Azhar University, Egypt

Email

mhessai@azhar.edu.eg

City

-

Orcid

0000-0002-0929-7053

First Name

Marina

Last Name

Magdy

MiddleName

-

Affiliation

Electronics & Communications Engineering Department, Higher Institute of Engineering and Technology, Luxor – El Tod, Egypt

Email

-

City

-

Orcid

-

Volume

46

Article Issue

No 5

Related Issue

16730

Issue Date

2018-09-01

Receive Date

2018-04-30

Publish Date

2018-09-01

Page Start

539

Page End

555

Print ISSN

1687-0530

Online ISSN

2356-8550

Article File

JESAUN_Volume 46_Issue No 5_Pages 539-555.pdf

PDF . 843.7kB

Link

https://jesaun.journals.ekb.eg/article_110510.html

Detail API

https://jesaun.journals.ekb.eg/service?article_code=110510

Order

1

Type

Research Paper

Type Code

1,438

Publication Type

Journal

Publication Title

JES. Journal of Engineering Sciences

Publication Link

https://jesaun.journals.ekb.eg/

MainTitle

EFFICIENT HARDWARE IMPLEMENATATIONS OF FEEDFORWARD NEURAL NETWORKS USING FIELD PROGRAMMABLE GATE ARRAY

Details

Type

Article

Created At

23 Jan 2023