| Jordan神经网络的改进研究 |
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| 引用本文： | 张宁,陈笑蓉.Jordan神经网络的改进研究[J].贵州大学学报(自然科学版),2009,26(1):36-39. |
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| 作者姓名： | 张宁 陈笑蓉 |
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| 作者单位： | 贵州大学计算机科学与技术学院,贵州,贵阳,550025 |
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| 摘 要： | 针对Jordan神经网络的反馈网络的反馈信息表征能力不强的缺点，提出了一种新的反馈网络模型，对Jordan神经网络的缺点进行了改进，并且对原来的训练学习算法进行了改进，提出了一种提取绝对值最大权的训练学习算法来降低计算复杂性，最终给出了实验结果证明。
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| 关 键 词： | 反馈网络 Jordan神经网络 复杂性 表征能力 |
The Improvement Studies on Jordan Neural Networks |
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| ZHANG Ning,CHEN Xiao-rong.The Improvement Studies on Jordan Neural Networks[J].Journal of Guizhou University(Natural Science),2009,26(1):36-39. |
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| Authors: | ZHANG Ning CHEN Xiao-rong |
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| Institution: | The College of Computer Science and Technology;Guizhou University;Guiyang 550025;China |
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| Abstract: | Aiming at the shortcomings of the recurrent network recurrent information characterization weak capacity about Jordan neural network,a new model of the recurrent network was proposed for improving the shortcomings about the Jordan neural network,and a a training learning algorithm extracting the greatest absolute value weight was proposed in order to reduce the complexity of calculating.For improving the original training learning algorithm,eventually this paper gives the experimental results to illustrate ... |
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| Keywords: | recurrent neutral network jordan neural networks complexity characterization capacity |
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