The equalizer is constructed with decision feedback structure, and an immune algorithm is used to determine the structure and parameters of RBF nonlinear hidden layer.
这种均衡器引入了判决反馈均衡器的结构，并采用免疫算法确定RBF网络隐层（非线性层）的结构和参数。
The principle and methods to determine the network parameters such as number of neuron in hidden layer, excitation function and the convergence accuracy have been analyzed in detail.
并且详细叙述了神经网络结构参数如隐含层神经元个数、激励函数、网络收敛精度等的确定原则和方法。
The main problems in designing a RBFNN depend on fixing the nodes of the hidden layer, the parameters of the centers and the linear weights.
设计中存在的主要问题包括隐层神经元数、中心和半径的确定，以及网络权值的训练。
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