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基于单输出型神经网络的血细胞分类研究

Blood cell’s classification based on single-output artificial neural network
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摘要 分别利用BP神经网络与单输出型神经网络对已经得到的血细胞特征参数进行计算,设计出分类器对血细胞进行自动分类识别。单输出型神经网络分类器与BP神经网络分类器相比,具有设计简单、收敛速度快、识别精度高且更加稳健的优点,取得了较好的应用效果。 The blood cell's characteristic parameters that have been obtained previously were processed with both BP Neural Network and Single-output Neural Network in order to classify the blood cells automatically. Compared with the BP Neural Network, the Single-output Neural Network is affirmed with more effective result due to a few advantages such as simpler design, faster convergence speed, higher accuracy of recognition and better robustness.
作者 毕峰
出处 《计算机应用》 CSCD 北大核心 2007年第6期1497-1499,1507,共4页 journal of Computer Applications
基金 国家自然科学基金资助项目(60372081)
关键词 模式识别 神经网络 分类器 pattern recognition artificial neural network olassifier
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参考文献6

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