Title: Multi-user detection based on RBF neural network hybrid hierarchy genetic algorithm
Abstract: One kind of hybrid hierarchy genetic algorithm to train the RBF neural network’s structure and parameters simultaneously is proposed, the improved chromosome code scheme is introduced, the least squares method based on singular value decomposition is used to compute weights of network’s output layer, the efficiency of genetic search is enhanced and the structure of the network is simplified. Finally it uses variable learning rate gradient descent method to optimize optimum network which is trained by genetic algorithm, then applied in the multiuser detection. The simulation indicates that structure of the network trained by the new hybrid learning algorithm is simpler than the network trained by the other algorithms and achieves good performance.
Publication Year: 2009
Publication Date: 2009-01-01
Language: en
Type: article
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