Open AccessAn Analysis of FPGA Hardware Platform Based Artificial Neural Network
Author(s) -
Ferry Wahyu Wibowo
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1201/1/012009
Subject(s) - field programmable gate array , computer science , artificial neural network , software , binary number , set (abstract data type) , computer hardware , computer architecture , embedded system , algorithm , artificial intelligence , mathematics , arithmetic , programming language
The artificial neural networks (ANN) algorithm is a mathematical model of a network by applying neurons and usually, it is represented as a directed graph with vertexes and edges. This algorithm is a paradigm of information processing to describe arbitrary functions and inspired by the biological nervous systems. This algorithm can learn a non-linearly separated set of outputs. A much software-based application has implemented this algorithm but the challenge in the hardware-based is still possible to do in mapping the output into binary values. This paper addressed on the platform of the hardware-based the ANN algorithm. The field programmable gate arrays (FPGAs) is closely related to this platform. The FPGAs have achieved a successful penetration in different multi-disciplinary domains.