Sparse Identification of Volterra Models for Power Amplifiers Without Pseudoinverse Computation-Reference-Cited by-同舟云学术

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Sparse Identification of Volterra Models for Power Amplifiers Without Pseudoinverse Computation

Published:2020-11 Issue:11 Volume:68 Page:4570-4578
ISSN:0018-9480
Container-title:IEEE Transactions on Microwave Theory and Techniques
language:
Short-container-title:IEEE Trans. Microwave Theory Techn.

Author:

Becerra Juan A.^ORCID,Ayora Maria Jose Madero^ORCID,Reina-Tosina Javier^ORCID,Crespo-Cadenas Carlos^ORCID

Funder

Spanish National Board of Scientific and Technological Research

European Regional Development Fund (ERDF) of the European Commission

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Condensed Matter Physics,Radiation

Link

http://xplorestaging.ieee.org/ielx7/22/9248689/09178996.pdf?arnumber=9178996

Cited by 19 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Complexity-Optimized Sample Selection for Fast Adaptation of Digital Predistorter;IEEE Transactions on Microwave Theory and Techniques;2024

2. Reducing Parameter Estimation Error of Behavioral Modeling and Digital Predistortion via Transfer Learning for RF Power Amplifiers;IEEE Transactions on Microwave Theory and Techniques;2023-11

3. Optimal Sparse Volterra Modeling for Transient Behavior of Turbofan Engines Based on Internet of Things;Journal of Circuits, Systems and Computers;2023-04-15

4. Beam-Level Frequency-Domain Digital Predistortion for OFDM Massive MIMO Transmitters;IEEE Transactions on Microwave Theory and Techniques;2023-04

5. A Digital Predistortion Technique Based on Improved Sparse Least Squares Twin Support Vector Regression br;J ELECTRON INF TECHN;2023

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