应用DEKF算法训练模糊化神经网络

乔士东 已出版文章查询
乔士东
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1 沈振康 已出版文章查询
沈振康
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1国防科技大学ATR国家重点实验室,湖南,长沙,410073


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模糊MLP网络的待定参数规模比确定性MLP网络的多几倍,急需找到高效的训练算法.本文尝试用DEKF训练模糊神经网络,这是DEKF算法新的应用.仿真表明,DEKF算法比经典BP算法的收敛速度更快,训练所得网络的精度更高.

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