Search

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. [ABSTRACT FROM AUTHOR]