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电子学报  2014 

模糊格构造型形态神经网络

, PP. 319-327

Keywords: 数学形态学,形态神经网络,模糊格,模式识别

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Abstract:

针对构造型形态神经网络(CMNN)决策函数的局限性,提出了一种模糊格构造型形态神经网络(FL-CMNN);该模型在利用训练好的CMNN进行分类时,引入模糊格包容性测度计算测试样本属于各超盒的隶属度值.采用仿真数据集对提出的FL-CMNN模型进行了评价,并与原始的CMNN和传统的人工神经网络、支持向量机、最近邻分类器进行了对比;试验结果表明,FL-CMNN在测试精度上明显优于原始的CMNN,训练时间远远低于传统的神经网络和支持向量机,而分类精度丝毫不亚于传统的神经网络和支持向量机.

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