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
fDate :
7/1/2003 12:00:00 AM
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;
Journal_Title :
Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on
DOI :
10.1109/TCSI.2003.813966
