TY - GEN
T1 - Online adaptive nonlinear channel equalization using RBF neural networks
AU - Junxia, Tian
AU - Liping, D. U.
AU - Jingming, Kuang
AU - Hua, Wang
PY - 2004
Y1 - 2004
N2 - Nonlinear distortions must be compensated in many real-life systems, which are encountered in digital satellite and microwave channels or others, so adaptive equalization is of considerable practical interest. Radial basis function neural networks have the ability to equalize nonlinear channels, and a simplified version of it is proposed to fit for online implement. We focus on stochastic gradient technique, and get a good performance by adjusting only one coefficient and one center closest to the input vector. Simulations are included to verify the algorithm.
AB - Nonlinear distortions must be compensated in many real-life systems, which are encountered in digital satellite and microwave channels or others, so adaptive equalization is of considerable practical interest. Radial basis function neural networks have the ability to equalize nonlinear channels, and a simplified version of it is proposed to fit for online implement. We focus on stochastic gradient technique, and get a good performance by adjusting only one coefficient and one center closest to the input vector. Simulations are included to verify the algorithm.
KW - Adaptive equalization(ae)
KW - Radical basis function(rbf)
KW - Stochastic gradient(sg)
UR - http://www.scopus.com/inward/record.url?scp=20844438194&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:20844438194
SN - 0780385624
T3 - ICCEA 2004 - 2004 3rd International Conference on Computational Electromagnetics and its Applications, Proceedings
SP - 300
EP - 303
BT - ICCEA 2004 - 2004 3rd International Conference on Computational Electromagnetics and its Applications, Proceedings
A2 - Benqing, G.
A2 - Xiaowen, X.
T2 - ICCEA 2004 - 2004 3rd International Conference on Computational Electromagnetics and its Applications
Y2 - 1 November 2004 through 4 November 2004
ER -