TY  - JOUR
T1  - Equalization Using Neural Network Applied for Multiple Access Technique in Differential Chaos Shift Keying
AU - , M.A. Ben Farah AU - , A. Kachouri AU - , M. Samet 
JO  - Journal of Engineering and Applied Sciences
VL  - 2
IS  - 6
SP  - 1097
EP  - 1102
PY  - 2007
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2007.1097.1102
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2007.1097.1102
KW  - MADCSK
KW  -RBF network
KW  -chaos
KW  -ISI
KW  -communication schemes
AB  - Using chaos for communication is a new field of research. Chaos communication has been studied for only a little more than a decade while traditional communication schemes have been developed for nearly a century. The hope was that for some application chaotic communication will prove to be better than traditional communication. In this study, a Multiple-access technique for use with Differential Chaos Shift Keying (MADCSK) is proposed and analyzed. A simple one-dimensional iterative map is used to generate the chaotic signals for all users and the average data rates for the users are identical. Bit-error rates are derived numerically for different number of users and computer simulations are performed to verify the results, we propose in this paper a novel method based on neural network, to improve the reception of MADCSK modulation. The Intersymbol Interference (ISI) degrades the performance of MADCSK systems through dispersive channels. We seek to correct this phenomenon by equalization techniques. Recently, neural networks become a solution for many problems in signal treatment. We choose RBF network to improve the performances of the signal and to correct the effect of channels.
ER  -