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基于v-支持向量回归机的盲均衡算法

Blind Equalization Algorithm Based on v-Support Vector Regressor
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摘要 盲均衡可以看作模式分类问题,每一类由信源字符表的可能输出定义。由于支持向量回归机具有优良的泛化性能,提出了一种基于v-支持向量回归机的盲均衡算法,并且利用加权最小二乘方法求解v-支持向量回归机。计算机仿真结果表明提出的盲均衡算法具有计算复杂度低、适于实际应用的特点。 The blind equalization can be seen as a pattern recognition problem, where each class is defined by the possible outcomes of the symbol alphabet. A new blind equalization algorithm using a v-support vector regressor （v-SVR） was developed because of the good generalization properties the SVR presents. A weighted least square procedure was proposed for attaining the v-SVR solutions. The performance of the proposed algorithm was evaluated via simulations and shown to have low computation complexity and implement easily.
作者 刘锋 葛临东
机构地区 解放军信息工程大学信息工程学院
出处 《系统仿真学报》 CAS CSCD 北大核心 2009年第10期2921-2924,共4页 Journal of System Simulation
基金 国家部级基金资助项目
关键词 支持向量回归机 盲均衡 加权最小二乘 泛化性能 support vector regressor blind equalization weighted least square generalization properties
分类号 TN911 [电子电信—通信与信息系统] TP391 [自动化与计算机技术—计算机应用技术]
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参考文献11

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系统仿真学报
2009年 第10期

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