Blind compensation of nonlinear distortions via sparsity recovery

@article{Duarte2012BlindCO,
  title={Blind compensation of nonlinear distortions via sparsity recovery},
  author={Leonardo Tomazeli Duarte and Ricardo Suyama and Romis de Faissol Attux and Jo{\~a}o Marcos Travassos Romano and Christian Jutten},
  journal={2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO)},
  year={2012},
  pages={2362-2366}
}
In this work, we address the problem of compensating a nonlinear memoryless system in a blind fashion, i.e., without considering a set of training points. Our proposal works with the assumption that the input signal admits a sparse representation in a transformed domain that should be known in advance. By assuming that the nonlinear distortion function makes the observed signal less sparse (this is observed in frequency transforms), the proposed method aims at estimating the original signal via… CONTINUE READING

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