Regular ArticleHyper Radial Basis Function Neural Networks for Interference Cancellation with Nonlinear Processing of Reference Signal
References (19)
- et al.
Interference cancellation using radial basis function networks
Signal Processing
(1995) Increased rates of convergence through learning rate adaptation
Neural Networks
(1988)Multilayer feedforward networks are universal approximators
Neural Networks
(1989)- et al.
Adaptive noise cancelling: Principles and applications
Proc. of the IEEE
(1975) - et al.
Adaptive Inverse Control
(1996) - et al.
Channel equalization using adaptive complex radial basis function networks
IEEE J. Selected Areas Comm.
(1995) - et al.
Performance evaluation of a sequential minimal radial basis function (RBF) neural network learning algorithm
IEEE Trans. Neural Networks
(1998) - et al.
Nonlinear filters for noise reduction
Proc. of Conf. on Signal Processing VII: Theories and Applications
(1994) - et al.
Noise cancelling with signal and reference correlated, using third order moments
Higher Order Statistics
(1992)
There are more references available in the full text version of this article.
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A. Cichocki is on leave from the Warsaw University of Technology, Poland.
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