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最速下降和共轭梯度混合算法在波束形成中的应用
引用本文:赵翠芹,段艳明,包玉珍.最速下降和共轭梯度混合算法在波束形成中的应用[J].河池师专学报,2011(5):97-100.
作者姓名:赵翠芹  段艳明  包玉珍
作者单位:[1]河池学院计算机与信息科学系,广西宜州546300 [2]云南科技信息职业学院,云南昆明650224
基金项目:广西自然科学基金资助项目(2011jjB70037); 河池学院青年科研经费资助课题(2011A-N008)
摘    要:介绍了一种最速下降法和共轭梯度法的混合算法,并将这种混合算法应用到自适应波束形成中。该方法根据最小均方(LMS)准则推导出代价函数,结合共轭梯度法和最速下降法产生搜索方向,既提高了共轭梯度算法的收敛速度,又解决了最速下降法下降缓慢的问题。计算机仿真表明,混合算法所需迭代次数少于最速下降法,且显著减少计算量,缩短运行时间。

关 键 词:最速下降法  共轭梯度法  自适应波束形成

An Application of a Hybrid Algorithm of the Steepest Descent Method and the Conjugate Gradient Method to Adaptive Beam Formation
ZHAO Cui-qin,DUAN Yang-ming,BAO Yu-zhen.An Application of a Hybrid Algorithm of the Steepest Descent Method and the Conjugate Gradient Method to Adaptive Beam Formation[J].Journal of Hechi Normal College,2011(5):97-100.
Authors:ZHAO Cui-qin  DUAN Yang-ming  BAO Yu-zhen
Institution:1.Department of Computer and Information Science,Hechi University,Yizhou,Guangxi 546300;2.Yunnan Vocational Institute of Scientific and Technological Information,Kunming,Yunnan 650224,China)
Abstract:A hybrid algorithm based on the steepest descent method and the conjugate gradient method is proposed,which is applied to adaptive beam formation.This method derives cost function based upon least mean square(LMS) criterion.The hybrid algorithm raises the convergence rate of the conjugate gradient method and solves the problem of slow descent of the steepest descent method.Computer simulations show that the proposed hybrid algorithm is superior to the steepest descent method in that it not only reduces the amount of calculation but also shortens the time of operation.
Keywords:steepest descent method  conjugate gradient method  adaptive beam formation
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