摘要: 以设计最小RBF网络结构为着眼点,提出了一种基于互信息的RBF神经网络结构优化算法。该算法用k近邻统计法估计隐节点输出矩阵与输出节点输出矩阵之间的互信息,获得每个隐节点与输出节点之间的相关性度量,删除相关性最小的隐节点,进而达到优化网络结构的目的。该算法具有自恢复机制,在简化网络结构的同时能有效保证网络的信息处理能力。在人工数据集和真实基准数据集上的仿真实验验证了该算法的有效性与稳定性。
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