Realization of Artificial Neural Networks on FPGA

被引：1

作者：

Ersoy, Mevlut ^{[1
]}

Kumral, Cem Deniz ^{[1
]}

机构：

[1] Suleyman Demirel Univ, Dept Comp Engn, Isparta, Turkey

来源：

ARTIFICIAL INTELLIGENCE AND APPLIED MATHEMATICS IN ENGINEERING PROBLEMS | 2020年 / 43卷

关键词：

Artificial Neural Networks; Field Programmable Gate Array; Very High Speed Integrated Circuit Hardware Description Language; Real time systems;

D O I：

10.1007/978-3-030-36178-5_31

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Artificial Neural Networks (ANNs) are generally modeled and used as software based. Software models are insufficient in real time applications where ANN output needs to be calculated. ANN has an architecture that can operate in parallel to calculate hidden layers. The fact that ANN has such an architecture makes it potentially fast in calculating certain transactions. However, the speed of these operations in real-time systems depends on the specification of the hardware. Therefore, ANN design has been realized on FPGA which is capable of parallel processing. In this way, the ANN structure was realized in a hardware structure and it was provided to be used on real-time structures.

引用

页码：418 / 428

页数：11

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