@inproceedings{48bd4b43c9f34f6694fd73b305301f0e,
title = "Multilayer perceptron network with integrated training algorithm in FPGA",
abstract = "In this manuscript we present the implementation of an artificial neural network type Multilayer Perceptron (ANN-MP or NNMP) in Field-Programmable Gate Arrays (FPGA), including Back-Propagation training method based on descendent gradient. This network has 2 reconfigurable hidden layers, adjustable parameters (epochs and ratio learning) and batch learning. The proposed architecture aims to reduce the number of logical elements to be used, so serial processing is utilized. In order to test the performance of the trained network, a nonlinear function was approximated with satisfactory results.",
keywords = "Artificial neural network, Back propagation, Descendent gradient, FPGA",
author = "P{\'e}rez-Garc{\'i}a, {A. N.} and Tornez-Xavier, {G. M.} and Flores-Nava, {L. M.} and F. G{\'o}mez-Casta{\~n}eda and Moreno-Cadenas, {J. A.}",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 11th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2014 ; Conference date: 29-09-2014 Through 03-10-2014",
year = "2014",
doi = "10.1109/ICEEE.2014.6978300",
language = "Ingl{\'e}s",
series = "2014 11th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2014 11th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2014",
address = "Estados Unidos",
}