Journal of Astronautics ›› 2012, Vol. 33 ›› Issue (8): 1127-1131.doi: 10.3873/j.issn.1000-1328.2012.08.018

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A Novel Wideband Beam Forming Method Based Generalized RegressionNeural Network Ensemble

ZHANG Zhen   

  1. 1. Department of Electronic Information, Jiangsu University of Science and Technology, Zhenjiang 212003, China;
    2. Department of Electronic Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
  • Received:2011-10-24 Revised:2012-03-21 Online:2012-08-15 Published:2012-08-23

Abstract: First, kernel principal component analysis (KPCA) method and the generalized regression neural network (GRNN) are optimized by using the particle swarm optimization (PSO) algorithm after the covariance matrix for beam forming is obtained. Second, optimized KPCA method is used to reduce the dimension of train samples in order to reduce the complexity of GRNN. Finally, considering both difference and correctness of every neural network weight coefficients for beam\|forming are obtained by using the proposed neural network ensemble method based fuzzy clustering method (FCM) and Heuristic idea. The simulation results show that the proposed method has good performance under a very simple structure of the neural network.

Key words: Neural network ensemble, Beam forming, Particle swarm optimization, Fuzzy clustering method, generalized reGression neural network(GRNN)

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