| 一种最小二乘／奇异值分解算法 |
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| 引用本文： | 曹新容,黄联芬,赵毅峰.一种最小二乘／奇异值分解算法[J].计算机工程,2009,35(16):278-279. |
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| 作者姓名： | 曹新容 黄联芬 赵毅峰 |
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| 作者单位： | 厦门大学信息科学与技术学院,厦门,361005 |
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| 摘 要： | 针对预失真技术中存在记忆非线性放大器预失真的问题，分析数字预失真器的结构和常用预失真器的识别算法，对经典最小二乘／奇异值分解（LS／SVD）算法进行改进，以较少资源获得较高性能。仿真结果表明，改进的LS／SVD算法能实现记忆非线性放大器的快速、高效线性化，提高记忆非线性放大器的性能。
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| 关 键 词： | 数字预失真 Hammerstein模型 最小二乘 奇异值分解 |
| 修稿时间： | |
Least Square/Singular Value Decomposition Algorithm |
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| CAO Xin-rong,HUANG Lian-fen,ZHAO Yi-feng.Least Square/Singular Value Decomposition Algorithm[J].Computer Engineering,2009,35(16):278-279. |
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| Authors: | CAO Xin-rong HUANG Lian-fen ZHAO Yi-feng |
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| Affiliation: | School of Information Science and Technology;Xiamen University;Xiamen 361005 |
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| Abstract: | Aiming at the problem of predistortion for memory nonlinear amplifier in predistortion technology,this paper analyzes the structure of digital predistortion and recognization algorithm of common predistortion,improves classical Least Square/Singular Value Decomposition(LS/SVD) algorithm.Improved LS/SVD algorithm can obtain better performance by less resource.Simulation results show the proposed algorithm can realize fast and effective linearization of memory nonlinear amplifier,and improve its performance. |
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| Keywords: | digital predistortion Hammerstein model Least Square(LS) Singular Value Decomposition(SVD) |
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