EURASIP Journal on Applied Signal Processing
Adaptive minimum error-rate filtering design: A review
Signal Processing
Symbol decision equalizer using a radial basis functions neural network
NN'06 Proceedings of the 7th WSEAS International Conference on Neural Networks
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III
Kernel least mean square algorithm with constrained growth
Signal Processing
Equalisation of satellite mobile channels with neural network techniques
Space Communications
IEEE Transactions on Neural Networks
Complex-valued function approximation using a fully complex-valued RBF (FC-RBF) learning algorithm
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Letters: Fully complex extreme learning machine
Neurocomputing
Complex-valued support vector classifiers
Digital Signal Processing
A neural network based data least squares algorithm for channel equalization
IEA/AIE'07 Proceedings of the 20th international conference on Industrial, engineering, and other applications of applied intelligent systems
Channel equalization using neural networks: a review
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
ADVIS'04 Proceedings of the Third international conference on Advances in Information Systems
Channel equalization using complex extreme learning machine with RBF kernels
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part III
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part III
Robust recursive complex extreme learning machine algorithm for finite numerical precision
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
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It is generally recognized that digital channel equalization can be interpreted as a problem of nonlinear classification. Networks capable of approximating nonlinear mappings can be quite useful in such applications. The radial basis function network (RBFN) is one such network. We consider an extension of the RBFN for complex-valued signals (the complex RBFN or CRBFN). We also propose a stochastic-gradient (SG) training algorithm that adapts all free parameters of the network. We then consider the problem of equalization of complex nonlinear channels using the CRBFN as part of an equalizer. Results of simulations we have carried out show that the CRBFN with the SG algorithm can be quite effective in channel equalization