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• W2600205733 abstract "This paper reports the identification of nonlinear models for wireless communications systems. The procedure relies on a novel complex-valued Volterra series (CVS) representation to provide a sparse representation based on statistical hypothesis testing and the Bayesian information criterion (BIC). The approach has been experimentally evaluated with the front-end of a communications transmitter taking into account the possible nonlinear impairments associated with the I/Q modulator. The proposed identification method showed an excellent performance in terms of model complexity reduction and dynamic range." @default.
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• W2600205733 date "2017-01-01" @default.
• W2600205733 modified "2023-10-03" @default.
• W2600205733 title "Identification of Volterra model parameters in wireless systems" @default.
• W2600205733 cites W1520105770 @default.
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• W2600205733 doi "https://doi.org/10.1109/pawr.2017.7875583" @default.
• W2600205733 hasPublicationYear "2017" @default.
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