DocumentCode :
2027197
Title :
Implementations approches of neural networks lane following system
Author :
Benjemmaa, Afef ; Klabi, Imen ; Masmoudi, Mohamed Slim ; El ouni, Jihed ; Masmoudi, Mohamed
Author_Institution :
METS Res. Group, Nat. Eng. Sch. of Sfax, Sfax, Tunisia
fYear :
2012
fDate :
25-28 March 2012
Firstpage :
515
Lastpage :
518
Abstract :
Nowadays, the techniques based on the use of artificial neural networks are instigating increasing interest in the fields of control and robotics. The rapidity of processing, the ability to learn and adapt as well as the robustness of these approaches, are motivating this work. To help this system be embedded in a wheelchair, it is imperative to respect the functional constraints and those of resource allocation, weights, consumption, cost... So conceiving an embedded system is ultimately an exercise in optimization: minimizing production costs for optimal functionality. The objective of this work is FPGA implementation of an optimal architecture of neuronal network.
Keywords :
cost reduction; embedded systems; field programmable gate arrays; mobile robots; neural nets; neurocontrollers; resource allocation; wheelchairs; FPGA; artificial neural network; embedded system; functional constraint; neural network lane following system; neuronal network architecture; optimal functionality; optimization; production cost minimization; resource allocation; robotics; robustness; weight consumption; wheelchair; Artificial neural networks; Biological neural networks; Encoding; Field programmable gate arrays; Least squares approximation; Polynomials; FPGA; Neuronal network; Optimization; lookup table approach; polynomial function; sigmoid function;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrotechnical Conference (MELECON), 2012 16th IEEE Mediterranean
Conference_Location :
Yasmine Hammamet
ISSN :
2158-8473
Print_ISBN :
978-1-4673-0782-6
Type :
conf
DOI :
10.1109/MELCON.2012.6196485
Filename :
6196485
Link To Document :
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