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Artículo
On the Optimum Number of Coefficients of Sparse Digital Predistorters: A Bayesian Approach
(IEEE, 2020-12)
This work presents insights on the application of the Bayesian information criterion (BIC) to fix the optimum number of coefficients in the Volterra series applied to the modeling and linearization of power amplifiers ...
Artículo
A Doubly Orthogonal Matching Pursuit Algorithm for Sparse Predistortion of Power Amplifiers
(IEEE, 2018-08)
This letter presents a new method for the digital predistortion (DPD) of power amplifiers (PAs) based on sparse behavioral models. The Gram-Schmidt orthogonalization is synergistically integrated into the orthogonal matching ...
Artículo
Sparse identification of volterra models for power amplifiers without pseudoinverse computation
(Institute of Electrical and Electronics Engineers Inc., 2021)
We present a new formulation of the doubly orthogonal matching pursuit (DOMP) algorithm for the sparse recovery of Volterra series models. The proposal works over the covariance matrices by taking advantage of the orthogonal ...
Artículo
A Sparse-Bayesian Approach for the Design of Robust Digital Predistorters Under Power-Varying Operation
(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2022)
In this article, a sparse-Bayesian treatment is proposed to solve the crucial questions posed by power amplifier (PA) and digital predistorter (DPD) modeling. To learn a model, the advanced Bayesian framework includes ...