基于自组织径向基网络的染色体分类
Classification of Human Chromosomes with An Organizing Radial Basis. Function Network
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摘要: 提出了一种基于自组织径向基人工神经元网络的人体染色体模式分类的方法,该方法将人体染色体长度、着丝点位置、带纹分布等特征作为自组织径向基网络的输入,利用自组织径向基网络的混合学习算法对网络进行训练,使人工神经元网络对人体染色体具有了自动分类的能力.Abstract: An approach to classify human chromosomes through an organizing radial basis function network (RBFN) is proposed. The three characteristics of chromosome, the length of the chromosome, the centromeric index and the density profile, are imployed to be the inputs of the organizing RBFN. With an hybrid learning algorithm, the organizing RBFN is tyained to classify the chromosomes. The relevant study results are of reference value in automatic classification of chromosome.