Application of Support Vector Regression in Beamforming
Support vector machine (SVM) has shown several advantages in prediction, regression, and estimation over some of the classical approaches. The new approach that support vector regression (SVR) applied to the array beamforming is proposed in this paper. Training data and test data on the effects of SVR Beamforming are researched. The new method has been applied in the environment of noise and interference, and is compared with uniform weighted beamforming. It has found that the array beamforming using SVR has the ability of suppression interference. Finally, effectiveness of the new method is verified through computer simulation.
SVM beamforming SVR
Cui Lin Li Yaan Li Xiaohua Liu Wangsheng
College of Marine Northwestern Polytechnical University Xian, China
国际会议
哈尔滨
英文
1270-1273
2011-12-24（万方平台首次上网日期，不代表论文的发表时间）