DocumentCode
1799933
Title
Implementation of a feed-forward Artificial Neural Network in VHDL on FPGA
Author
Dondon, Philippe ; Carvalho, Julien ; Gardere, Remi ; Lahalle, Paul ; Tsenov, Georgi ; Mladenov, Valeri
Author_Institution
ENSEIRB-MATMECA, Ecole Nat. Super. d´Electron., France
fYear
2014
fDate
25-27 Nov. 2014
Firstpage
37
Lastpage
40
Abstract
Describing an Artificial Neural Network (ANN) using VHDL allows a further implementation of such a system on FPGA. Indeed, the principal point of using FPGA for ANNs is flexibility that gives it an advantage toward other systems like ASICS which are entirely dedicated to one unique architecture and allowance to parallel programming, which is inherent to ANN calculation system and one of their advantages. Usually FPGAs do not have unlimited logical resources integrated in a single package and this limitation forcesrequirement for optimizations for the design in order to have the best efficiency in terms of speed and resource consumption. This paper deals with the VHDL designing problems which can be encountered when trying to describe and implement such ANNs on FPGAs.
Keywords
feedforward neural nets; field programmable gate arrays; hardware description languages; parallel programming; ANN calculation system; ASICS; FPGA; VHDL designing problems; feedforward artificial neural network; logical resources; parallel programming; resource consumption; Artificial neural networks; Biological neural networks; Field programmable gate arrays; MATLAB; Neurons; Random access memory; Read only memory; FPGA implementation; VHDL; neural networks; nonlinear systems;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Network Applications in Electrical Engineering (NEUREL), 2014 12th Symposium on
Conference_Location
Belgrade
Print_ISBN
978-1-4799-5887-0
Type
conf
DOI
10.1109/NEUREL.2014.7011454
Filename
7011454
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