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Recognition of Continuous Digits by Quantum Neural Networks

Recognition of Continuous Digits by Quantum Neural Networks
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摘要 This paper describes a new kind of neural network-Quantum Neural Network(QNN) and its application to recognition of continuous digits. QNN combines the advantages of neuralmodeling and fuzzy theoretic principles . Experiment results show that more than 15 percent errorreduction is achieved on a speaker-independent continuous digits recognition task compared with BPnetworks. This paper describes a new kind of neural network-Quantum Neural Network(QNN) and its application to recognition of continuous digits. QNN combines the advantages of neuralmodeling and fuzzy theoretic principles . Experiment results show that more than 15 percent errorreduction is achieved on a speaker-independent continuous digits recognition task compared with BPnetworks.
作者 LI Fei, ZHAO Sheng-mei, ZHENG Bao-yu (Institute of Signal & Information Processing, Nanjing University of Posts and Telecommunications, Nanjing 210003, P.R. China)
出处 《The Journal of China Universities of Posts and Telecommunications》 EI CSCD 2003年第1期29-33,共5页 中国邮电高校学报（英文版）
基金 theScienceandTechnologyFoundationoftheEducationDepartmentofJiangsuProvince (No.2 0 0 1 1 9)
关键词 quantum neural net-work quantum neuron speech recognition quantum neural net-work quantum neuron speech recognition
分类号 TP183 [自动化与计算机技术—控制理论与控制工程]
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参考文献15

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The Journal of China Universities of Posts and Telecommunications
2003年 第1期

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