DocumentCode
1234820
Title
A neural-network-based channel-equalization strategy for chaos-based communication systems
Author
Feng, Jiuchao ; Tse, Chi K. ; Lau, Francis C M
Author_Institution
Hong Kong Polytech. Univ., China
Volume
50
Issue
7
fYear
2003
fDate
7/1/2003 12:00:00 AM
Firstpage
954
Lastpage
957
Abstract
This work 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 incorporating a specific training (equalizing) algorithm.
Keywords
AWGN; chaotic communication; distortion; equalisers; learning (artificial intelligence); recurrent neural nets; telecommunication channels; telecommunication computing; channel distortion problem; channel equalization; chaos-based communication systems; neural-network-based equalization strategy; recurrent neural networks; training algorithm; AWGN; Additive white noise; Autoregressive processes; Chaotic communication; Communication systems; Equalizers; Gaussian noise; Nonlinear distortion; Recurrent neural networks; Wideband;
fLanguage
English
Journal_Title
Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on
Publisher
ieee
ISSN
1057-7122
Type
jour
DOI
10.1109/TCSI.2003.813966
Filename
1211097
Link To Document