Estimation and equalization of fading channels with random coefficients
Signal Processing - Special issue on higher order statistics
Blind and semi-blind equalization using hidden Markov models and clustering techniques
Signal Processing - Special issue on current topics in adaptive filtering for hands-free acoustic communication and beyond
Equalization of satellite UMTS channels using neural network devices
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 05
Equalisation of satellite mobile channels with neural network techniques
Space Communications
Nonlinear blind equalization schemes using complex-valued multilayer feedforward neural networks
IEEE Transactions on Neural Networks
A practical radial basis function equalizer
IEEE Transactions on Neural Networks
A complex valued radial basis function network for equalization of fast time varying channels
IEEE Transactions on Neural Networks
Optimal adaptive k-means algorithm with dynamic adjustment of learning rate
IEEE Transactions on Neural Networks
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This paper provides a comparative study of several non-linear blind equalizers in terms of computational requirements and of the transient performance, which is the main criterion to be considered in the context of time-varying channels. Computational requirements are estimated as the number of real additions and multiplications associated with the training algorithm, whereas the transient performance is evaluated in terms of convergence time. The impact of local minima on the tracking ability is carefully evaluated, in terms of a suitable criterion proposed in the paper. Simulations involve both single-layer (linear and polynomial filters), as well as multilayer structures (radial basis function, recurrent network, multilayer perceptron). These techniques are applied to the blind equalization of mobile terrestrial and satellite channels. Guidelines are established for the choice of a suitable structure as the major trade-off to be achieved in a mobile context is between computational effort and robustness of tracking capability (with respect to local minima effects).