The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Un certain nombre de schémas de communication utilisant le chaos ont été proposés ces dernières années. Quelle que soit la méthode de modulation exacte utilisée, le signal transmis doit passer par un canal physique qui introduit de manière indésirable une distorsion dans le signal et y ajoute du bruit. Le problème est particulièrement grave lorsqu'une démodulation cohérente est utilisée car le processus nécessaire de synchronisation du chaos est difficile à mettre en œuvre dans la pratique. Cet article aborde le problème de distorsion des canaux et propose une technique d'égalisation des canaux dans les systèmes de communication basés sur le chaos. L'égalisation proposée est réalisée par un réseau neuronal récurrent modifié (RNN) incorporant un algorithme d'entraînement (égalisation) spécifique. Des simulations informatiques sont utilisées pour démontrer les performances de l'égaliseur proposé dans les systèmes de communication basés sur le chaos. La carte Henon et le circuit de Chua sont utilisés pour générer des signaux chaotiques. Il est démontré que l'égaliseur basé sur RNN proposé surpasse les égaliseurs conventionnels.
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Copier
Jiu-chao FENG, Chi Kong TSE, Francis C. M. LAU, "Channel Equalization for Chaos-Based Communication Systems" in IEICE TRANSACTIONS on Fundamentals,
vol. E85-A, no. 9, pp. 2015-2024, September 2002, doi: .
Abstract: A number of schemes have been proposed for communication using chaos over the past years. Regardless of the exact modulation method used, the transmitted signal must go through a physical channel which undesirably introduces distortion to the signal and adds noise to it. The problem is particularly serious when coherent-based demodulation is used because the necessary process of chaos synchronization is difficult to implement in practice. This paper addresses the channel distortion problem and proposes a technique for channel equalization in chaos-based communication systems. The proposed equalization is realized by a modified recurrent neural network (RNN) incorporating a specific training (equalizing) algorithm. Computer simulations are used to demonstrate the performance of the proposed equalizer in chaos-based communication systems. The Henon map and Chua's circuit are used to generate chaotic signals. It is shown that the proposed RNN-based equalizer outperforms conventional equalizers.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e85-a_9_2015/_p
Copier
@ARTICLE{e85-a_9_2015,
author={Jiu-chao FENG, Chi Kong TSE, Francis C. M. LAU, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Channel Equalization for Chaos-Based Communication Systems},
year={2002},
volume={E85-A},
number={9},
pages={2015-2024},
abstract={A number of schemes have been proposed for communication using chaos over the past years. Regardless of the exact modulation method used, the transmitted signal must go through a physical channel which undesirably introduces distortion to the signal and adds noise to it. The problem is particularly serious when coherent-based demodulation is used because the necessary process of chaos synchronization is difficult to implement in practice. This paper addresses the channel distortion problem and proposes a technique for channel equalization in chaos-based communication systems. The proposed equalization is realized by a modified recurrent neural network (RNN) incorporating a specific training (equalizing) algorithm. Computer simulations are used to demonstrate the performance of the proposed equalizer in chaos-based communication systems. The Henon map and Chua's circuit are used to generate chaotic signals. It is shown that the proposed RNN-based equalizer outperforms conventional equalizers.},
keywords={},
doi={},
ISSN={},
month={September},}
Copier
TY - JOUR
TI - Channel Equalization for Chaos-Based Communication Systems
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2015
EP - 2024
AU - Jiu-chao FENG
AU - Chi Kong TSE
AU - Francis C. M. LAU
PY - 2002
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E85-A
IS - 9
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - September 2002
AB - A number of schemes have been proposed for communication using chaos over the past years. Regardless of the exact modulation method used, the transmitted signal must go through a physical channel which undesirably introduces distortion to the signal and adds noise to it. The problem is particularly serious when coherent-based demodulation is used because the necessary process of chaos synchronization is difficult to implement in practice. This paper addresses the channel distortion problem and proposes a technique for channel equalization in chaos-based communication systems. The proposed equalization is realized by a modified recurrent neural network (RNN) incorporating a specific training (equalizing) algorithm. Computer simulations are used to demonstrate the performance of the proposed equalizer in chaos-based communication systems. The Henon map and Chua's circuit are used to generate chaotic signals. It is shown that the proposed RNN-based equalizer outperforms conventional equalizers.
ER -