然后,通过RPCL(Rival Penalized Competitive Learning)聚类分析划分训练样本空间从而形成训练样本集,并以支持向量机(SVM)作为识别器,试验结果证明了该方法的有效性。
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... 关键词: 粒子群优化(PSO)算法；改进粒子群优化(MPSO)算法；径向基函数(RBF)神经 网络；混沌优化算法；对手受罚的竞争学习(RPCL)算法 [gap=1192]ptimization; radial basis function neural network; chaos optimization algorithm; rival penalized competit...
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Therefore, RPCL is utilized to converge some of initial centers to actual centers of original color image and image is segmented by these learned cluster centers.
因此，本文采用RPCL算法，对这些组合的聚类中心颜色进行学习来确定实际的颜色类数目以及聚类中心，并用学习后的聚类中心对原图像进行聚类分割。
This paper proposes to overcome those problems by incorporating the improved RPCL (rival penalized competitive learning)algorithm and the EM(expectation maximization)algorithm into the EBF structure.
本文提出用结合改进的RPCL算法和EM算法的EBF网络结构来解决上述问题。
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