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The radial basis function neural network (RBFNN) is a feedforward neural network; it has great advantages over the MLP (multilayer perceptron) in the approximation and classification. However it is difficult to construct a simple and efficient NN with learning algorithm, that is, there are so many parameters to determine. A novel IEA-RBFNN multiuser detector is presented based on the immune theory in biology. The goal of the algorithm is to solve the contradiction of the complexity and the performance of the RBF-NN in the application in CDMA. Simulations show that the algorithm can converge rapidly and effectively eliminate multi-access interference, so it is near-far resistant.